QIT Module Library

QIT has many modules available on the command line interface through qit and in the 3D viewer through qitview. This page below provides an index of the publicly available modules.

AffineCompose

Compose two affine transforms

Input:

Flag	Type	Description
`--inner`	Affine	input inner
`--outer`	Affine	input outer

Output:

Flag	Type	Description
`--output`	Affine	output affine

AffineConvert

Convert an affine transform between file formats

Input:

Flag	Type	Description
`--input`	Affine	input affine

Output:

Flag	Type	Description
`--output`	Affine	output affine

AffineCreate

Create an affine transform based on user specified parameters

Parameters:

Flag	Type	Default	Description
`--transX`	double	`0.0`	(optional) translation in x
`--transY`	double	`0.0`	(optional) translation in y
`--transZ`	double	`0.0`	(optional) translation in z
`--rotX`	double	`0.0`	(optional) rotation axis in x
`--rotY`	double	`0.0`	(optional) rotation axis in y
`--rotZ`	double	`0.0`	(optional) rotation axis in z
`--rotA`	double	`0.0`	(optional) rotation angle
`--scaleX`	double	`1.0`	(optional) scaleCamera in x
`--scaleY`	double	`1.0`	(optional) scaleCamera in y
`--scaleZ`	double	`1.0`	(optional) scaleCamera in z
`--skewX`	double	`0.0`	(optional) skew in x
`--skewY`	double	`0.0`	(optional) skew in y
`--skewZ`	double	`0.0`	(optional) skew in z

Output:

Flag	Type	Description
`--output`	Affine	output affine

AffineInvert

Invert an affine transform

Input:

Flag	Type	Description
`--input`	Affine	input affine

Output:

Flag	Type	Description
`--output`	Affine	output affine

AffinePrintInfo

Print basic information about an affine transform

Input:

Flag	Type	Description
`--input`	Affine	the input affine

AffineReduce

Reduce an affine transform to a simpler affine transform in one of several possible ways

Input:

Flag	Type	Description
`--input`	Affine	an affine transform

Parameters:

Flag	Type	Description
`--translation`	flag	(optional) include the translation part
`--linear`	flag	(optional) include the linear part
`--orthogonalize`	flag	(optional) orthogonalize the linear part

Output:

Flag	Type	Description
`--output`	Affine	output affine

CurvesAttributeMap

Compute an attribute map, that is, a volume that represents the most likely value of a given curves attribute for each voxel.

Input:

Flag	Type	Description
`--input`	Curves	input curves
`--refvolume`	Volume	(optional) input reference volume (exclusive with refmask)
`--refmask`	Mask	(optional) input reference mask (exclusive with refvolume)

Parameters:

Flag	Type	Default	Description
`--attr`	String	`attr`	(optional) the name of attribute to extract from the curves
`--threads`	int	`1`	(optional) the number of threads

Output:

Flag	Type	Description
`--output`	Volume	output attribute map
`--outputDensity`	Volume	(optional) output density map
`--outputMask`	Mask	(optional) output mask

CurvesAttributes

Manipulate curves vertex attributes. Operations support comma-delimited lists

Input:

Flag	Type	Description
`--input`	Curves	the input curves

Parameters:

Flag	Type	Description
`--copy`	String	(optional) copy attribute (x=y syntax)
`--rename`	String	(optional) rename attribute (x=y syntax)
`--remove`	String	(optional) remove attribute (- for all)
`--retain`	String	(optional) retain the given attributes and remove others)

Output:

Flag	Type	Description
`--output`	Curves	the output curves

CurvesBox

Compute a bounding box from curves

Input:

Flag	Type	Description
`--input`	Curves	input curves

Output:

Flag	Type	Description
`--output`	Solids	output box

CurvesCat

Concatenate multiple curves datasets to a single larger dataset

Input:

Flag	Type	Description
`--a`	Curves	input curves a
`--b`	Curves	(optional) input curves b
`--c`	Curves	(optional) input curves c
`--d`	Curves	(optional) input curves d
`--e`	Curves	(optional) input curves e
`--f`	Curves	(optional) input curves f

Output:

Flag	Type	Description
`--output`	Curves	output curves

CurvesCatPattern

Concatenate curves using a filename pattern

Parameters:

Flag	Type	Default	Description
`--pattern`	String		a pattern to read curves filenames (should contains %s for substitution)
`--names`	String		a list of identifiers (will be substituted in the input pattern)
`--along`	String		(optional) optionally use the given attribute to account for along bundle parameterization
`--bundleName`	String	`bundle_name`	(optional) use the given bundle attribute/field name
`--alongName`	String	`along_name`	(optional) use the given along attribute/field name
`--bundleIndex`	String	`bundle_index`	(optional) use the given bundle attribute/field index
`--alongIndex`	String	`along_index`	(optional) use the given along attribute/field index

Output:

Flag	Type	Description
`--curves`	Curves	the output combined curves
`--table`	Table	the table to store labels

CurvesClusterFeature

Cluster curves using simple curve features (length, endpoints, position, shape) using K-means

Input:

Flag	Type	Description
`--input`	Curves	the input curves

Parameters:

Flag	Type	Default	Description
`--length`	flag		(optional) include the length
`--endpoints`	flag		(optional) include tensor product of endpoints
`--gaussian`	flag		(optional) include the Gaussian shape
`--num`	Integer	`2`	(optional) the number of clusters
`--thresh`	Double		(optional) the threshold size for clusters (enables DP-means)

Advanced Parameters:

Flag	Type	Default	Description
`--iters`	Integer	`100`	(optional) the maxima number of iterations
`--restarts`	Integer		(optional) the number of restarts
`--relabel`	flag		(optional) relabel to reflect cluster size
`--largest`	flag		(optional) keep only the largest cluster

Output:

Flag	Type	Description
`--output`	Curves	(optional) the output curves
`--protos`	Curves	(optional) the prototypical curves for each cluster

CurvesClusterGraph

Curve bundle segmentation with graph-based thresholding

Input:

Flag	Type	Description
`--input`	Curves	the input curves

Parameters:

Flag	Type	Default	Description
`--dist`	String	`meanhaus`	(optional) the name of the inter-curve distance
`--thresh`	double	`1.0`	(optional) the threshold for grouping

Advanced Parameters:

Flag	Type	Default	Description
`--largest`	flag		(optional) retain the largest group
`--relabel`	flag		(optional) relabel to reflect cluster size

Output:

Flag	Type	Description
`--output`	Curves	the output curves

Citation: Felzenszwalb, P. F., & Huttenlocher, D. P. (2004). Efficient graph-based image segmentation. International journal of computer vision, 59(2), 167-181.

CurvesClusterHierarchical

Cluster curves with hierarchical clustering.

Input:

Flag	Type	Description
`--input`	Curves	the input curves

Parameters:

Flag	Type	Default	Description
`--dist`	String	`meanhaus`	(optional) the name of the inter-curve distance
`--num`	Integer		(optional) the number of clusters
`--thresh`	Double		(optional) the threshold for grouping

Advanced Parameters:

Flag	Type	Description
`--density`	Double	(optional) resample the curves to speed up computation
`--epsilon`	Double	(optional) simplify the curves to speed up computation
`--relabel`	flag	(optional) relabel to reflect cluster size

Output:

Flag	Type	Description
`--output`	Curves	the output curves

Citation: Zhang, S., Correia, S., & Laidlaw, D. H. (2008). Identifying white-matter fiber bundles in DTI data using an automated proximity-based fiber-clustering method. IEEE transactions on visualization and computer graphics, 14(5), 1044-1053.

CurvesClusterQuickBundle

Cluster curves with the quicksbundles algorithm

Input:

Flag	Type	Description
`--input`	Curves	the input curves

Parameters:

Flag	Type	Default	Description
`--subset`	Integer		(optional) take a subset of curves before clustering (not applicable if you provide fewer)
`--samples`	Integer	`5`	(optional) the number of sample vertices
`--thresh`	Double	`1000.0`	(optional) the separation threshold

Advanced Parameters:

Flag	Type	Default	Description
`--relabel`	flag		(optional) relabel to reflect cluster size

Output:

Flag	Type	Description
`--output`	Curves	(optional) the output curves
`--centers`	Curves	(optional) the output centers (the centroid curves for each cluster)

Citation: Garyfallidis, E., Brett, M., Correia, M. M., Williams, G. B., & Nimmo-Smith, I. (2012). Quickbundles, a method for tractography simplification. Frontiers in neuroscience, 6, 175.

CurvesClusterSCPT

Cluster curves with a sparse closest point transform.

Input:

Flag	Type	Description
`--input`	Curves	the input curves

Parameters:

Flag	Type	Default	Description
`--subset`	Integer		(optional) take a subset of curves before clustering (not applicable if you provide fewer)
`--thresh`	Double	`22.0`	(optional) the threshold size for clusters
`--largest`	flag		(optional) retain only the largest cluster
`--fraction`	Double		(optional) retain only clusters that are a given proportion of the total (zero to one)
`--iters`	Integer	`100`	(optional) the maxima number of iterations

Advanced Parameters:

Flag	Type	Default	Description
`--preeps`	Double	`1.0`	(optional) preprocess by simplifying the curves
`--lmsub`	Integer	`5000`	(optional) the number of curves for landmarking
`--lmeps`	Double	`1.0`	(optional) the simplifification threshold for landmarking
`--lmthresh`	Double	`30.0`	(optional) the landmarking threshold
`--restarts`	Integer		(optional) the number of restarts
`--num`	Integer	`2`	(optional) the number of clusters

Output:

Flag	Type	Description
`--output`	Curves	(optional) the output curves
`--landmarks`	Vects	(optional) the computed landmarks
`--protos`	Curves	(optional) the prototypical curves for each cluster

CurvesClusterSpectral

Cluster curves with spectral clustering.

Input:

Flag	Type	Description
`--input`	Curves	the input curves

Parameters:

Flag	Type	Default	Description
`--dist`	String	`meanhaus`	(optional) the name of the inter-curve distance
`--num`	Integer		(optional) the number of clusters

Advanced Parameters:

Flag	Type	Description
`--density`	Double	(optional) resample the curves to speed up computation
`--epsilon`	Double	(optional) simplify the curves to speed up computation
`--relabel`	flag	(optional) relabel to reflect cluster size

Output:

Flag	Type	Description
`--output`	Curves	the output curves

Citation: Cluster curves with spectral clustering. O’Donnell, L. J., & Westin, C. F. (2007). Automatic tractography segmentation using a high-dimensional white matter atlas. IEEE transactions on medical imaging, 26(11), 1562-1575.

CurvesCompare

Compare a pair of curves objects quantitatively

Input:

Flag	Type	Description
`--left`	Curves	input curves
`--right`	Curves	the other curves

Parameters:

Flag	Type	Default	Description
`--delta`	double	`1.0`	(optional) the volume resolution
`--thresh`	double	`0.5`	(optional) the density threshold

Output:

Flag	Type	Description
`--output`	Table	output table

CurvesConnectRegions

Extract the connecting segments between the given regions

Input:

Flag	Type	Description
`--input`	Curves	input curves
`--regions`	Mask	input regions (should have two distinct labels)

Parameters:

Flag	Type	Default	Description
`--shortest`	flag		(optional) extract only the shortest connection
`--simple`	flag		(optional) extract only simple connections

Output:

Flag	Type	Description
`--output`	Curves	output curves

CurvesConvert

Convert curves between file formats

Input:

Flag	Type	Description
`--input`	Curves	input curves

Output:

Flag	Type	Description
`--output`	Curves	output curves

CurvesCreateHelix

Create a curves dataset consisting of a helix bundle

Parameters:

Flag	Type	Default	Description
`--radius`	double	`10.0`	(optional) the radius of the helix
`--length`	double	`5.0`	(optional) the length of one loop of the helix
`--loops`	int	`2`	(optional) the number of loops in the helix
`--steps`	int	`100`	(optional) the number of steps sampled along each loop of the helix
`--sigma`	double	`1.0`	(optional) the width of the helix bundle
`--samples`	int	`1`	(optional) the number of samples in the helix bundle
`--startx`	double	`0.0`	(optional) the starting position in x
`--starty`	double	`0.0`	(optional) the starting position in y
`--startz`	double	`0.0`	(optional) the starting position in z

Output:

Flag	Type	Description
`--output`	Curves	output curves

CurvesCrop

Crop curves to retain only portions inside the selection

Input:

Flag	Type	Description
`--input`	Curves	the input curves
`--mask`	Mask	(optional) a mask
`--solids`	Solids	(optional) some solids

Parameters:

Flag	Type	Default	Description
`--invert`	flag		(optional) invert the selection
`--and`	flag		(optional) require that curves are inside all solids (logical AND)
`--attr`	String		(optional) specify an attribute for cropping
`--above`	Double		(optional) require that the given attribute at each vertex is above this value
`--below`	Double		(optional) require that the given attribute at each vertex is below this value
`--equals`	Double		(optional) require that the given attribute approximately equals this value
`--delta`	Double	`0.001`	(optional) the threshold distance for approximate cropping

Output:

Flag	Type	Description
`--output`	Curves	the output curves

CurvesCull

Cull redundant curves. This can be done using SCPT (scpt) or pairwise distance-based clustering (haus, cham, end, or cutoff). DistanceExtrinsic based clustering is much slower but technically more accurate.

Input:

Flag	Type	Description
`--input`	Curves	the input curves

Parameters:

Flag	Type	Default	Description
`--dist`	String	`scpt`	(optional) the name of the inter-curve distance (scpt, haus, cham, end, or cutoff). Pairwise distances can be symmeterized by adding mean, min, or max to the name (except scpt).
`--thresh`	Double	`1.5`	(optional) the threshold for removal in mm (but the exact meaning of this depends on the distance metric, so be careful)

Output:

Flag	Type	Description
`--output`	Curves	the output curves

Citation: Zhang, S., Correia, S., & Laidlaw, D. H. (2008). Identifying white-matter fiber bundles in DTI data using an automated proximity-based fiber-clustering method. IEEE transactions on visualization and computer graphics, 14(5), 1044-1053.

CurvesDensity

Compute a volumetric density of curves. This works by find the voxels that intersect the curves and accumulating how many curves intersected each voxel.

Input:

Flag	Type	Description
`--input`	Curves	input curves
`--reference`	Volume	(optional) input reference volume (exclusive with refmask)

Parameters:

Flag	Type	Default	Description
`--type`	CurvesDensityType	`Count`	(optional) specify the type of normalization (Options: Count, CountNorm, Color, ColorNorm)

Advanced Parameters:

Flag	Type	Default	Description
`--delta`	double	`1.0`	(optional) when no reference sampling is present, create a volume with this voxel size

Output:

Flag	Type	Description
`--output`	Volume	output density volume

CurvesEndpointMask

Extract curve endpoints and create a mask

Input:

Flag	Type	Description
`--input`	Curves	input curves
`--reference`	Volume	(optional) input reference volume

Parameters:

Flag	Type	Default	Description
`--head`	int	`1`	(optional) curve head label
`--tail`	int	`2`	(optional) curve tail label
`--num`	int	`1`	(optional) use the given number of vertices from the endpoints
`--dilate`	int	`0`	(optional) dilate the endpoint mask
`--mode`	flag		(optional) apply a mode filter

Output:

Flag	Type	Description
`--output`	Mask	output mask

CurvesEndpoints

Extract curve endpoints and return them as vects

Input:

Flag	Type	Description
`--input`	Curves	input curves

Parameters:

Flag	Type	Default	Description
`--head`	flag		(optional) curve head vertices
`--tail`	flag		(optional) curve tail vertices

Output:

Flag	Type	Description
`--output`	Vects	output vects

CurvesExtract

Extract only curves that match a given attribute value

Input:

Flag	Type	Description
`--input`	Curves	input curves

Parameters:

Flag	Type	Default	Description
`--attr`	String	`label`	(optional) the attribute name of the label used to select
`--which`	String	``	(optional) which labels to extract, e.g. 1,2,3:5

Output:

Flag	Type	Description
`--output`	Curves	output curves

CurvesFeatures

Compute features of curves and add them as vertex attributes

Input:

Flag	Type	Description
`--input`	Curves	the input curves

Parameters:

Flag	Type	Description
`--tangent`	flag	(optional) compute tangents
`--color`	flag	(optional) compute vertex colors
`--arclength`	flag	(optional) compute per-vertex arclength
`--index`	flag	(optional) compute per-vertex index
`--fraction`	flag	(optional) compute per-vertex fraction along curve
`--count`	flag	(optional) compute per-curve vertex count
`--length`	flag	(optional) compute per-curve length
`--frame`	flag	(optional) compute the per-vertex frenet frame
`--curvature`	flag	(optional) compute the per-vertex curvatures
`--density`	flag	(optional) compute the per-vertex density
`--stats`	flag	(optional) compute the per-curve statistics of vertex curvature and density

Advanced Parameters:

Flag	Type	Default	Description
`--all`	flag		(optional) compute all possible features
`--voxel`	double	`1.0`	(optional) specify a voxel size used for computing density

Output:

Flag	Type	Description
`--output`	Curves	the output curves

CurvesFilterKernel

Filter curves with kernel regression. This uses a non-parametric statistical approach to smooth the curves

Input:

Flag	Type	Description
`--input`	Curves	input curves

Parameters:

Flag	Type	Default	Description
`--density`	Double		(optional) resample with a given vertex density (mm/vertex), otherwise the original arclength sampling is used
`--sigma`	Double	`4.0`	(optional) use the given spatial bandwidth
`--order`	int	`0`	(optional) specify the order of the local approximating polynomial
`--thresh`	Double	`0.05`	(optional) the threshold for excluding data from local regression
`--attrs`	String	`coord`	(optional) the attributes to smooth (comma separated list)

Output:

Flag	Type	Description
`--output`	Curves	output curves

CurvesFilterLoess

Filter curves with lowess smoothing

Input:

Flag	Type	Description
`--input`	Curves	input curves

Parameters:

Flag	Type	Default	Description
`--density`	Double		(optional) resample with a given vertex density (mm/vertex), otherwise the original arclength sampling is used
`--num`	int	`5`	(optional) use the given neighborhood size for local estimation
`--order`	Integer	`2`	(optional) use a given polynomial order for local estimation
`--endpoints`	flag		(optional) smooth endpoints

Output:

Flag	Type	Description
`--output`	Curves	output curves

CurvesFilterPolynomial

Filter cures with polynomial splines

Input:

Flag	Type	Description
`--input`	Curves	input curves

Parameters:

Flag	Type	Default	Description
`--density`	Double		(optional) resample with a given vertex density (mm/vertex), otherwise the original arclength sampling is used
`--lambda`	Double		(optional) use regularization Tikhonov regularization (specify the negative log, so and input of 2.3 would give a regularization weight of 0.1)
`--order`	Integer	`10`	(optional) use a given polynomial order
`--residual`	flag		(optional) save the residuals

Output:

Flag	Type	Description
`--output`	Curves	output curves
`--outputResiduals`	Vects	(optional) output residual error between the polynomial and the curve

CurvesFilterPredicate

Filter curves with kernel regression. This uses a non-parametric statistical approach to smooth the curves

Input:

Flag	Type	Description
`--input`	Curves	input curves

Parameters:

Flag	Type	Default	Description
`--min`	int	`2`	(optional) The minimum number of vertices of the retained segments
`--nodot`	flag		(optional) Replace any dots in the attribute name with an underscore, e.g. pval.age would become pval_age
`--predicate`	String	`pval < 0.05`	(optional) the predicate for determining if a vertex should be kept

Output:

Flag	Type	Description
`--output`	Curves	output curves

CurvesFilterTOM

Filter curves based on their agreement with a tract orientation map

Input:

Flag	Type	Description
`--input`	Curves	the input curves
`--reference`	Volume	(optional) input reference volume

Parameters:

Flag	Type	Default	Description
`--iters`	int	`1`	(optional) the number of iterations
`--beta`	double	`1.0`	(optional) a gain factor for computing likelihoods
`--thresh`	double	`0.05`	(optional) a threshold for outlier rejection
`--orient`	flag		(optional) orient the bundle prior to mapping
`--vector`	flag		(optional) compute a vector orientation (you may want to enable the orient flag)
`--norm`	VolumeEnhanceContrastType	`Histogram`	(optional) specify a method for normalizing orientation magnitudes (Options: Histogram, Ramp, RampGauss, Mean, None)
`--smooth`	flag		(optional) apply fiber smoothing after mapping

Advanced Parameters:

Flag	Type	Default	Description
`--sigma`	Double		(optional) apply smoothing with the given amount (bandwidth in mm) (default is largest voxel dimension)
`--support`	int	`3`	(optional) the smoothing filter radius in voxels

Output:

Flag	Type	Description
`--output`	Curves	the output inlier curves
`--tom`	Volume	(optional) input reference volume

CurvesFilterTTF

Filter curves to enhance their topographic regularity using the group graph spectral distance

Input:

Flag	Type	Description
`--input`	Curves	the input curves

Parameters:

Flag	Type	Default	Description
`--K`	Integer	`20`	(optional) size of neighborhood
`--sigma`	Double	`0.01`	(optional) parameter for the exponential in the proximity measure
`--density`	double	`5.0`	(optional) the resolution for downsampling curves

Output:

Flag	Type	Description
`--output`	Curves	the output curves

Citation: Wang, J., Aydogan, D. B., Varma, R., Toga, A. W., & Shi, Y. (2018). Modeling topographic regularity in structural brain connectivity with application to tractogram filtering. NeuroImage.

CurvesLabelMap

Compute a label map, that is, a mask that represents the most likely label of a given curves label for each voxel.

Input:

Flag	Type	Description
`--input`	Curves	input curves
`--refvolume`	Volume	(optional) input reference volume (exclusive with refmask)
`--refmask`	Mask	(optional) input reference mask (exclusive with refvolume)

Parameters:

Flag	Type	Default	Description
`--attr`	String	`label`	(optional) the name of attribute to extract from the curves
`--largest`	flag		(optional) filter out largest components
`--dilate`	int	`0`	(optional) dilate the mask a given number of times
`--threads`	int	`1`	(optional) the number of threads

Output:

Flag	Type	Description
`--output`	Mask	output label map
`--outputProb`	Volume	(optional) output probability map

CurvesLandmarks

Generate landmarks from curves using simplification and vertex clustering

Input:

Flag	Type	Description
`--input`	Curves	the input curves

Parameters:

Flag	Type	Default	Description
`--subsamp`	Integer	`1000`	(optional) the number of curves to subsample
`--eps`	Double	`2.0`	(optional) the spatial threshold for simplificaion
`--radius`	Double		(optional) the diameter of clusters for vertex grouping
`--num`	Integer	`2`	(optional) the number of clusters to start with

Output:

Flag	Type	Description
`--output`	Vects	the output landmarks

Citation: (in preparation)

CurvesLengths

Compute the lengths of the given curves

Input:

Flag	Type	Description
`--input`	Curves	the input curves

Output:

Flag	Type	Description
`--output`	Vects	the output landmarks

CurvesMask

Compute a volumetric mask of curves. Any voxel that intersects the curves will be included

Input:

Flag	Type	Description
`--input`	Curves	input curves
`--refvolume`	Volume	(optional) input reference volume (exclusive with refmask)
`--refmask`	Mask	(optional) input reference mask (exclusive with refvolume)

Parameters:

Flag	Type	Default	Description
`--thresh`	double	`0.5`	(optional) the threshold

Output:

Flag	Type	Description
`--output`	Mask	output mask

CurvesMaskMap

Measure how many curves overlap a given mask parcellation

Input:

Flag	Type	Description
`--input`	Curves	input curves
`--regions`	Mask	input regions
`--lookup`	Table	use a lookup for region names

Parameters:

Flag	Type	Default	Description
`--nameField`	String	`name`	(optional) specify the lookup table name field
`--indexField`	String	`index`	(optional) specify the lookup table index field
`--mode`	CurvesMaskMapMode	`Binary`	(optional) specify the way that curves are counted (Options: Count, Binary, Fraction)
`--endpoints`	flag		(optional) select only curves with endpoints in the mask

Output:

Flag	Type	Description
`--output`	Table	output table

CurvesMaskSelect

Select curves using volumetric masks

Input:

Flag	Type	Description
`--input`	Curves	input curves
`--deform`	Deformation	(optional) a deformation between curves and the masks
`--include`	Mask	(optional) use an include mask (AND for multiple labels)
`--exclude`	Mask	(optional) use an exclude mask (AND for multiple labels)
`--contain`	Mask	(optional) use a containment mask

Parameters:

Flag	Type	Default	Description
`--binarize`	flag		(optional) binarize the include mask
`--invert`	flag		(optional) invert the exclude mask
`--skip`	flag		(optional) skip masks without regions or an insufficient number of regions without error
`--thresh`	Double	`0.8`	(optional) specify a containment threshold
`--endpoints`	flag		(optional) select based on only curve endpoints
`--connect`	flag		(optional) select curves with endpoints that connect different labels

Output:

Flag	Type	Description
`--output`	Curves	the output curves

CurvesMath

Evaluate a mathematical expression at each vertex of curves.

Input:

Flag	Type	Description
`--input`	Curves	the input curves

Parameters:

Flag	Type	Default	Description
`--expression`	String	`x > 0.5`	(optional) the expression to evaluate
`--result`	String	`result`	(optional) the attribute name for the result

Output:

Flag	Type	Description
`--output`	Curves	output curves

CurvesMeasure

Measure statistics of curves and store the results in a table

Input:

Flag	Type	Description
`--input`	Curves	input curves

Parameters:

Flag	Type	Default	Description
`--delta`	double	`1.0`	(optional) the volume resolution
`--thresh`	double	`0.5`	(optional) the density threshold

Advanced Parameters:

Flag	Type	Default	Description
`--advanced`	flag		(optional) add advanced measures (outlier measures). warning: these take polynomial time with the number of curves
`--endcor`	flag		(optional) add the endpoint correlation measure
`--neighbors`	int	`16`	(optional) specify a number of neighbors for topographic measures
`--samples`	int	`5000`	(optional) specify a number of samples for endpoint correlations estimation

Output:

Flag	Type	Description
`--output`	Table	output table

CurvesMidpointMask

Extract curve endpoints and return them as vects

Input:

Flag	Type	Description
`--input`	Curves	input curves
`--reference`	Volume	(optional) input reference volume

Parameters:

Flag	Type	Default	Description
`--label`	int	`1`	(optional) the mask label
`--num`	int	`1`	(optional) use the given number of vertices from the midpoint
`--dilate`	int	`0`	(optional) dilate the endpoint mask

Output:

Flag	Type	Description
`--output`	Mask	output mask

CurvesNearest

Extract the nearest curve to a collection

Input:

Flag	Type	Description
`--input`	Curves	input curves
`--ref`	Curves	reference curves
`--deform`	Deformation	(optional) a deformation for the input curve

Output:

Flag	Type	Description
`--output`	Curves	output curves

CurvesOrient

Orient curves to best match endpoints, i.e. flip them to make the starts and ends as close as possible

Input:

Flag	Type	Description
`--input`	Curves	input curves

Parameters:

Flag	Type	Default	Description
`--iters`	int	`10`	(optional) a maxima number of iterations
`--axis`	flag		(optional) orient to the nearest spatial axis

Output:

Flag	Type	Description
`--output`	Curves	output curves

CurvesOrientationMap

Compute an orientation map. This will find the most likely direction in each voxel

Input:

Flag	Type	Description
`--input`	Curves	input curves
`--refvolume`	Volume	(optional) input reference volume (exclusive with refmask)
`--refmask`	Mask	(optional) input reference mask (exclusive with refvolume)

Parameters:

Flag	Type	Default	Description
`--orient`	flag		(optional) orient the bundle prior to mapping
`--vector`	flag		(optional) compute a vector orientation (you may want to enable the orient flag)
`--norm`	VolumeEnhanceContrastType	`Histogram`	(optional) specify a method for normalizing orientation magnitudes (Options: Histogram, Ramp, RampGauss, Mean, None)
`--smooth`	flag		(optional) apply fiber smoothing after mapping
`--fibers`	flag		(optional) return a fibers volume

Advanced Parameters:

Flag	Type	Default	Description
`--sigma`	Double	`-1.0`	(optional) apply smoothing with the given amount (bandwidth in mm) (a negative value will use the largest voxel dimension)
`--support`	int	`3`	(optional) the smoothing filter radius in voxels

Output:

Flag	Type	Description
`--output`	Volume	output volume

CurvesOutlierGaussian

Filter outliers using a mvGaussian probabilistic model with a Chi2 distribution on the Mahalanobis distance

Input:

Flag	Type	Description
`--input`	Curves	the input curves
`--reference`	Curves	input reference curve

Parameters:

Flag	Type	Default	Description
`--outlierCount`	Integer	`10`	(optional) the number of points used for outlier rejection
`--outlierThresh`	Double	`0.95`	(optional) the probability threshold for outlier rejection

Output:

Flag	Type	Description
`--output`	Curves	the output curves

CurvesOutlierLength

Detect outliers among curves based on their length. In practice an absolute z-threshold of 2.0 should work well.

Input:

Flag	Type	Description
`--input`	Curves	the input curves

Parameters:

Flag	Type	Description
`--zthresh`	Double	(optional) specify an absolute threshold z-score
`--zlow`	Double	(optional) specify a low threshold z-score
`--zhigh`	Double	(optional) specify a high threshold z-score

Output:

Flag	Type	Description
`--inlier`	Curves	(optional) the output inlier curves
`--outlier`	Curves	(optional) the output outlier curves

CurvesOutlierSCPT

Detect outliers among curves with a sparse closest point transform.

Input:

Flag	Type	Description
`--input`	Curves	the input curves

Parameters:

Flag	Type	Default	Description
`--type`	String	`diagonal`	(optional) covariance matrix type (full, diagonal, spherical)
`--thresh`	Double	`0.99`	(optional) the threshold probability

Advanced Parameters:

Flag	Type	Default	Description
`--prior`	Double	`0.001`	(optional) the prior bundle size (mm)
`--mix`	Double	`0.0`	(optional) the prior mixing weight (use zero for no prior)

Output:

Flag	Type	Description
`--inlier`	Curves	(optional) the output inlier curves
`--outlier`	Curves	(optional) the output outlier curves
`--landmarks`	Vects	(optional) the computed landmarks

CurvesPrintInfo

Print basic information about curves

Input:

Flag	Type	Description
`--input`	Curves	the input curves

Parameters:

Flag	Type	Default	Description
`--stats`	flag		(optional) print statistics
`--length`	flag		(optional) print statistics of curve lengths

CurvesPrototype

Extract a prototypical curve that has maximum track density

Input:

Flag	Type	Description
`--input`	Curves	input curves

Parameters:

Flag	Type	Default	Description
`--delta`	double	`1.0`	(optional) the volume resolution

Output:

Flag	Type	Description
`--output`	Curves	output curves

CurvesReduce

Reduce the number of curves by random subsampling

Input:

Flag	Type	Description
`--input`	Curves	input curves

Parameters:

Flag	Type	Description
`--count`	Integer	(optional) a maxima number of curves
`--fraction`	Double	(optional) remove a given fraction of the curves
`--min`	Integer	(optional) retain at least this many curves

Output:

Flag	Type	Description
`--output`	Curves	output selected curves

CurvesRelabel

Relabel curves from biggest to smallest cluster

Input:

Flag	Type	Description
`--input`	Curves	the input curves

Parameters:

Flag	Type	Default	Description
`--threshold`	Double		retain only clusters above a given proportion of the total
`--largest`	flag		(optional) keep only the largest label

Output:

Flag	Type	Description
`--output`	Curves	the output curves

CurvesResample

Resample the position of vertices along curves so that they have uniform spacing

Input:

Flag	Type	Description
`--input`	Curves	input curves

Parameters:

Flag	Type	Description
`--num`	Integer	(optional) resample with a constant number of vertices per curve (0 specifices that the max should be used)
`--orient`	flag	(optional) reorient curves
`--density`	Double	(optional) resample with a given vertex density (mm/vertex)

Output:

Flag	Type	Description
`--output`	Curves	output curves

CurvesSample

Sample a volume at the vertices of curves

Input:

Flag	Type	Description
`--input`	Curves	the input curves
`--volume`	Volume	the volume

Parameters:

Flag	Type	Default	Description
`--interp`	InterpolationType	`Trilinear`	(optional) interpolation method (Options: Nearest, Trilinear, Tricubic, Gaussian, GaussianLocalLinear, GaussianLocalQuadratic)
`--attr`	String	`sampled`	(optional) attribute name

Output:

Flag	Type	Description
`--output`	Curves	the output curves

CurvesSegmentAlong

Segment a bundle by matching vertices along its length based on a prototype curve

Input:

Flag	Type	Description
`--input`	Curves	the input curves
`--proto`	Curves	(optional) input prototype curve (if not supplied, one will be computed)
`--deform`	Deformation	(optional) a deformation to transform the proto curves to the coordinates of the input curves

Parameters:

Flag	Type	Default	Description
`--method`	CurvesSegmentAlongType	`Hybrid`	(optional) the method for segmenting along the bundle (Options: Arclength, Distance, Hybrid)
`--samples`	Integer		(optional) the number of points used for along tract mapping (if not supplied, the number of points in the proto will be used)
`--density`	Double		(optional) the density of points used for along tract mapping (if not supplied, the number of points in the proto will be used)
`--label`	String	`label`	(optional) an attribute name for the label used to indicate the position along the bundle
`--outlier`	flag		(optional) remove outliers
`--outlierCount`	Integer	`10`	(optional) the number of points used for outlier rejection
`--outlierThresh`	Double	`0.99`	(optional) the probability threshold for outlier rejection
`--outlierAttrs`	String	`FA,MD,frac,diff,S0,base`	(optional) use the following attributes for outlier detection (if they exist)

Advanced Parameters:

Flag	Type	Default	Description
`--delta`	Double	`1.0`	(optional) the volume resolution for distance segmentation
`--power`	Double	`4.0`	(optional) the power for the mixing function (must be a positive even number, e.g. 2, 4, 6)

Output:

Flag	Type	Description
`--output`	Curves	the output curves
`--outputDist`	Volume	(optional) output distance volume (not provided by arclength segmentation)
`--outputLabel`	Volume	(optional) output label volume (not provided by arclength segmentation
`--outputProto`	Curves	(optional) output proto curve (useful in case it was computed automatically)
`--outputCore`	Curves	(optional) output core curve (the nearest curve to the prototype)

CurvesSelect

Select a which of curves using a number of possible criteria

Input:

Flag	Type	Description
`--input`	Curves	input curves
`--deform`	Deformation	(optional) a deformation between curves and the masks
`--mask`	Mask	(optional) a mask
`--solids`	Solids	(optional) some solids
`--vects`	Vects	(optional) some vects

Parameters:

Flag	Type	Default	Description
`--radius`	double	`5.0`	(optional) vects radius
`--or`	flag		(optional) use OR (instead of AND) to combine selections
`--invert`	flag		(optional) invert the selection after combining
`--exclude`	flag		(optional) exclude the selected curves
`--endpoints`	flag		(optional) select based on only curve endpoints
`--expression`	String		(optional) select based on a boolean-valued expression using any of: length, size, min_attr, max_attr, mean_attr, or sum_attr
`--minlen`	Double		(optional) a minimum length
`--maxlen`	Double		(optional) a maximum length
`--longest`	flag		(optional) select the longest curve

Output:

Flag	Type	Description
`--output`	Curves	output selected curves

CurvesSetAttributeLookupTable

Set vertex attributes of curves based on a table. The curves should have a discrete-valued attribute that is used to match vertices to entries in the table.

Input:

Flag	Type	Description
`--curves`	Curves	input curves
`--table`	Table	input table
`--lookup`	Table	(optional) a lookup table to relate names to indices

Parameters:

Flag	Type	Default	Description
`--mergeTable`	String	`name`	(optional) a table field name to merge on
`--mergeLookup`	String	`along_name`	(optional) a lookup field name to merge on
`--index`	String	`along_index`	(optional) the lookup table index field name
`--value`	String	`value`	(optional) a table field to get
`--cindex`	String		(optional) the curves index field name (defaults to lookup table index field name)
`--cvalue`	String		(optional) a curves field to set (defaults to table field name)
`--background`	double	`0.0`	(optional) a background value
`--missing`	Double		(optional) an missing value

Advanced Parameters:

Flag	Type	Default	Description
`--exclude`	flag		(optional) exclude data with no entry in the table

Output:

Flag	Type	Description
`--output`	Curves	output curves

CurvesSetAttributeVects

Set vertex attributes of curves based on a table. The curves should have a discrete-valued attribute that is used to match vertices to entries in the table.

Input:

Flag	Type	Description
`--curves`	Curves	input curves
`--vects`	Vects	input vectors

Parameters:

Flag	Type	Default	Description
`--name`	String	`attr`	(optional) an attribute field name
`--quiet`	flag		(optional) don’t complain if the vects and curves don’t match (and try to add as much data to the curves as possible)

Output:

Flag	Type	Description
`--output`	Curves	output curves

CurvesSimplify

Simplify curves with the Ramer-Douglas-Peucker algorithm

Input:

Flag	Type	Description
`--input`	Curves	the input curves

Parameters:

Flag	Type	Default	Description
`--epsilon`	double	`2.0`	(optional) the distance threshold
`--radial`	flag		(optional) use radial distance

Output:

Flag	Type	Description
`--output`	Curves	the output simplified curves

Citation: Heckbert, Paul S.; Garland, Michael (1997). Survey of polygonal simplification algorithms

CurvesSmooth

Smooth out irregularities in the input curves using laplacian (or Taubin) smoothing. This works best if curve vertices are equally spaced along each curve.

Input:

Flag	Type	Description
`--input`	Curves	input curves

Parameters:

Flag	Type	Default	Description
`--attr`	String	`coord`	(optional) the attribute to smooth
`--iters`	int	`1`	(optional) number of iterations
`--lambda`	double	`0.3`	(optional) lambda smoothing parameter

Advanced Parameters:

Flag	Type	Default	Description
`--mu`	Double		(optional) mu smoothing parameter (for Taubin smoothing)

Output:

Flag	Type	Description
`--output`	Curves	output curves

CurvesSubdivide

Subdivide the curves by inserting vertices in each edge

Input:

Flag	Type	Description
`--input`	Curves	input curves

Parameters:

Flag	Type	Default	Description
`--num`	Integer	`1`	(optional) subdivide the curves a given number of times

Output:

Flag	Type	Description
`--output`	Curves	output curves

CurvesSymmetrize

Make a left/right pair of curves symmetric

Input:

Flag	Type	Description
`--inputLeft`	Curves	input left curves
`--inputRight`	Curves	input right curves
`--reference`	Volume	input reference

Output:

Flag	Type	Description
`--outputLeft`	Curves	output left curves
`--outputRight`	Curves	output right curves

CurvesThickness

Compute the thickness of a bundle

Input:

Flag	Type	Description
`--input`	Curves	input curves
`--core`	Curves	(optional) input core

Output:

Flag	Type	Description
`--output`	Curves	output core with thickness

CurvesTransform

Apply a spatial transformation to curves

Input:

Flag	Type	Description
`--input`	Curves	input curves
`--affine`	Affine	(optional) apply an affine xfm
`--invaffine`	Affine	(optional) apply an inverse affine xfm
`--deform`	Deformation	(optional) apply a deformation xfm
`--pose`	Volume	(optional) apply a transform to match the pose of a volume
`--invpose`	Volume	(optional) apply a transform to match the inverse pose of a volume

Parameters:

Flag	Type	Description
`--reverse`	flag	(optional) reverse the order, i.e. compose the affine(deform(x)), whereas the default is deform(affine(x))
`--tx`	Double	(optional) translate the curves in the x dimension
`--ty`	Double	(optional) translate the curves in the y dimension
`--tz`	Double	(optional) translate the curves in the z dimension
`--sx`	Double	(optional) scale the curves in the x dimension
`--sy`	Double	(optional) scale the curves in the y dimension
`--sz`	Double	(optional) scale the curves in the z dimension

Output:

Flag	Type	Description
`--output`	Curves	output curves

CurvesTrkPrintHeader

Print basic information about TrackVis curves

Parameters:

Flag	Type	Default	Description
`--input`	String		the input curves filename

CurvesTubes

Create a mesh representing 3D tubes based on the input curves

Input:

Flag	Type	Description
`--input`	Curves	the input curves
`--affine`	Affine	(optional) apply an affine xfm
`--invaffine`	Affine	(optional) apply an inverse affine xfm
`--deform`	Deformation	(optional) apply a deformation xfm

Parameters:

Flag	Type	Default	Description
`--color`	flag		(optional) use per-vertex orientation coloring
`--wash`	Double	`0.2`	(optional) the color wash
`--dthick`	Double	`0.15`	(optional) the default tube thickness
`--fthick`	Double	`1.0`	(optional) the tube thickness factor (scales the thickness attribute, it it is present)
`--thick`	String	`thickness`	(optional) use the given thickness attribute
`--resolution`	int	`5`	(optional) the tube resolution
`--noColor`	flag		(optional) skip color attributes
`--noThick`	flag		(optional) skip thickness attributes
`--smooth`	flag		(optional) create smooth tube caps (the default will use a separate disk for tube caps)

Output:

Flag	Type	Description
`--output`	Mesh	the output tubes

CurvesVertices

Extract all curve vertices

Input:

Flag	Type	Description
`--input`	Curves	input curves

Output:

Flag	Type	Description
`--output`	Vects	output vects

CurvesVoxelize

Compute a mask by voxelizing curves. This works by find the voxels that intersect the curves and marking them as one.

Input:

Flag	Type	Description
`--input`	Curves	input curves
`--refvolume`	Volume	(optional) input reference volume (exclusive with refmask)
`--refmask`	Mask	(optional) input reference mask (exclusive with refvolume)

Output:

Flag	Type	Description
`--output`	Mask	output mask

GradientsCat

Concatenate two sets of gradients into one

Input:

Flag	Type	Description
`--input`	Gradients	input gradients
`--cat`	Gradients	gradients to concatenate
`--catB`	Gradients	(optional) gradients to concatenate
`--catC`	Gradients	(optional) gradients to concatenate
`--catD`	Gradients	(optional) gradients to concatenate

Output:

Flag	Type	Description
`--output`	Gradients	output concatenated gradients

GradientsConvert

Convert gradients between file formats

Input:

Flag	Type	Description
`--input`	Gradients	the input gradients

Output:

Flag	Type	Description
`--output`	Gradients	the output gradients

GradientsCreate

Create a gradients file from separate bvecs and bvals

Input:

Flag	Type	Description
`--bvecs`	Vects	the input bvecs
`--bvals`	Vects	the input bvals

Output:

Flag	Type	Description
`--output`	Gradients	the output gradients

GradientsMatch

Correct for errors in the orientation of diffusion gradients using the fiber coherence index

Input:

Flag	Type	Description
`--input`	Gradients	the input gradients
`--dwi`	Volume	the input diffusion-weighted MR volume
`--mask`	Mask	(optional) the input mask

Parameters:

Flag	Type	Default	Description
`--nospat`	flag		(optional) skip spatial scaling (note: this is not included in the paper by Schilling et al)

Output:

Flag	Type	Description
`--output`	Gradients	the output matched gradients

Citation: Schilling, Kurt G., et al. “A fiber coherence index for quality control of B-table orientation in diffusion MRI scans.” Magnetic resonance imaging (2019).

GradientsReduce

Reduce a set of gradients to a which based on user specification

Input:

Flag	Type	Description
`--input`	Gradients	the input gradients

Parameters:

Flag	Type	Description
`--which`	String	(optional) include only specific gradients (comma separated zero-based indices)
`--exclude`	String	(optional) exclude specific gradients (comma separated zero-based indices)
`--shells`	String	(optional) include only specific shells

Output:

Flag	Type	Description
`--output`	Gradients	the output gradients

GradientsTransform

Transform gradient directions (note: the order of operations is transpose, flip, swap, perm, affine)

Input:

Flag	Type	Description
`--input`	Gradients	input gradients
`--affine`	Affine	(optional) apply an affine transform to gradient directions (and normalize afterwards)

Parameters:

Flag	Type	Default	Description
`--round`	flag		(optional) round the gradients magnitudes
`--rounder`	int	`100`	(optional) specify how coarsely to round the gradient magnitudes
`--subset`	String		(optional) select a subset of gradients
`--flip`	String		(optional) flip a coodinate (x, y, or z)
`--swap`	String		(optional) swap a pair of coordinates (xy, xz, or yz)
`--perm`	String		(optional) permute by coordinate index, e.g. 1,0,2

Output:

Flag	Type	Description
`--output`	Gradients	output transformed gradients

MapEddy

Summarize the motion parameters from FSL EDDY

Input:

Flag	Type	Description
`--input`	Vects	the input eddy motion file, e.g. ‘eddy_movement_rms’

Parameters:

Flag	Type	Default	Description
`--prefix`	String	``	(optional) a prefix to add before the metric name

Output:

Flag	Type	Description
`--output`	Table	output map

MapLaterality

Compute the lateralization index of a given map. This assumes you have a two column table (name,value) that contains left and right measurements (see module parameters to specify the left/right identifiers)

Input:

Flag	Type	Description
`--input`	Table	input table (should use the naming convention like the module parameters)

Parameters:

Flag	Type	Default	Description
`--name`	String	`name`	(optional) the field holding the name of the measurement
`--value`	String	`value`	(optional) the field holding the value of the measurement
`--left`	String	`lh_`	(optional) the identifier for left values
`--right`	String	`rh_`	(optional) the identifier for right values
`--indlat`	String	`indlat_`	(optional) the identifier for the lateralization index
`--abslat`	String	`abslat_`	(optional) the identifier for the absolute lateralization index
`--unilat`	String	`unilat_`	(optional) the identifier for the unilateral averaging
`--minlat`	String	`minlat_`	(optional) the identifier for the left right minimum
`--maxlat`	String	`maxlat_`	(optional) the identifier for the left right maximum

Output:

Flag	Type	Description
`--output`	Table	output table

MaskAdapt

Clean a mask by performing morphological opening followed by closing

Input:

Flag	Type	Description
`--input`	Mask	input mask
`--volume`	Volume	input volume

Parameters:

Flag	Type	Default	Description
`--diameter`	int	`1`	(optional) the distance in voxels for adaptation
`--thresh`	double	`1.0`	(optional) the statistical threshold
`--robust`	flag		(optional) use robust statistics
`--robustHuber`	flag		(optional) use a Huber estimator robust statistics

Output:

Flag	Type	Description
`--output`	Mask	output mask
`--outputProb`	Volume	output prob

MaskBinarize

Binarize a mask to convert all labels to zero or one.

Input:

Flag	Type	Description
`--input`	Mask	input mask

Output:

Flag	Type	Description
`--output`	Mask	output mask

MaskBoundary

Close a mask using morphological operations

Input:

Flag	Type	Description
`--input`	Mask	input mask

Parameters:

Flag	Type	Default	Description
`--element`	String	`cross`	(optional) specify an element

Output:

Flag	Type	Description
`--output`	Mask	output mask

MaskBox

Compute the bounding box of a mask

Input:

Flag	Type	Description
`--input`	Mask	input mask

Parameters:

Flag	Type	Default	Description
`--foreground`	flag		(optional) compute box around foreground
`--buffer`	Double		(optional) a buffer in mm

Output:

Flag	Type	Description
`--output`	Solids	output bounding box

MaskBoxCreate

Create a mask from a box

Input:

Flag	Type	Description
`--input`	Solids	the input box

Parameters:

Flag	Type	Default	Description
`--delta`	double	`1.0`	(optional) voxel spacing
`--round`	flag		(optional) round the starting point

Output:

Flag	Type	Description
`--output`	Mask	output mask

MaskCentroids

Extract the centroids for each mask label

Input:

Flag	Type	Description
`--input`	Mask	input mask
`--mask`	Mask	(optional) restrict the centroids to the given mask
`--nearest`	Vects	(optional) extract only the centroid nearest to the given vector

Parameters:

Flag	Type	Default	Description
`--components`	flag		(optional) extract centroids of connected components
`--largest`	flag		(optional) extract only the largest centroid

Output:

Flag	Type	Description
`--output`	Vects	output vects

MaskClean

Clean a mask by performing morphological opening followed by closing

Input:

Flag	Type	Description
`--input`	Mask	input mask

Parameters:

Flag	Type	Default	Description
`--num`	int	`1`	(optional) the number of iterations
`--largest`	flag		(optional) select the largest component as an intermediate step
`--element`	String	`cross`	(optional) specify an element: cross, cube, or sphere. you can also specify an optional size, e.g. cross(3)
`--outside`	flag		(optional) treat voxels outside mask as background

Output:

Flag	Type	Description
`--output`	Mask	output mask

MaskClose

Close a mask morphologically. This dilates and then erodes the mask

Input:

Flag	Type	Description
`--input`	Mask	input mask

Parameters:

Flag	Type	Default	Description
`--num`	int	`1`	(optional) the number of times to erode and dilate the mask
`--largest`	flag		(optional) select the largest component as an intermediate step between erosion and dilation
`--mode`	flag		(optional) apply a mode filter as an intermediate step between erosion and dilation
`--element`	String	`cross`	(optional) specify an element: cross, cube, or sphere. you can also specify an optional size, e.g. cross(3)
`--outside`	flag		(optional) treat voxels outside mask as background

Output:

Flag	Type	Description
`--output`	Mask	output mask

MaskComponents

Compute connected components of a mask. The output will be sorted by the number of voxels per component, e.g. the largest component will have label 1, and the second largest will have label 2, etc.

Input:

Flag	Type	Description
`--input`	Mask	input mask

Parameters:

Flag	Type	Description
`--full`	flag	(optional) use a full 27-voxel neighborhood (default is 6-voxel)
`--which`	String	(optional) include only specific component labels, e.g. “1,2” would select the two largest components
`--minvoxels`	Integer	(optional) filter out components with fewer then the given number of voxels
`--minvolume`	Double	(optional) filter out components that are smaller in volume than the given threshold
`--keep`	flag	(optional) keep the input labels (only relevant to filtering options)

Output:

Flag	Type	Description
`--output`	Mask	output mask

MaskConvert

Convert a mask between file formats

Input:

Flag	Type	Description
`--input`	Mask	input

Output:

Flag	Type	Description
`--output`	Mask	output

MaskCreate

Create a mask based on user specified parameters

Parameters:

Flag	Type	Default	Description
`--deltax`	double	`1.0`	(optional) voxel spacing in x
`--deltay`	double	`1.0`	(optional) voxel spacing in y
`--deltaz`	double	`1.0`	(optional) voxel spacing in z
`--numx`	int	`128`	(optional) number of voxels in x
`--numy`	int	`128`	(optional) number of voxels in y
`--numz`	int	`1`	(optional) number of voxels in z
`--startx`	double	`0.0`	(optional) starting position in x
`--starty`	double	`0.0`	(optional) starting position in y
`--startz`	double	`0.0`	(optional) starting position in z
`--label`	int	`0`	(optional) constant label

Output:

Flag	Type	Description
`--output`	Mask	output mask

MaskCreateOverlay

Create a mask from an overlay file

Input:

Flag	Type	Description
`--reference`	Mask	input reference mask

Parameters:

Flag	Type	Default	Description
`--overlay`	String		the overlay filename
`--label`	int	`1`	(optional) the label to use
`--preserve`	flag		(optional) preserve the labels from the reference mask

Output:

Flag	Type	Description
`--output`	Mask	output mask

MaskCrop

Crop a mask down to a smaller mask (only one criteria per run)

Input:

Flag	Type	Description
`--input`	Mask	input mask
`--mask`	Mask	(optional) a mask
`--solids`	Solids	(optional) some soids

Parameters:

Flag	Type	Default	Description
`--range`	String		(optional) a range specification, e.g. start:end,start:end,start:end
`--invert`	flag		(optional) invert the selection
`--pad`	int	`0`	(optional) a padding size in voxels

Output:

Flag	Type	Description
`--output`	Mask	the output mask

MaskDeform

Dilate a mask morphologically.

Input:

Flag	Type	Description
`--input`	Mask	input mask

Parameters:

Flag	Type	Default	Description
`--effect`	double	`1.0`	(optional) deformation effect size
`--extent`	double	`1.0`	(optional) deformation spatial extent
`--iters`	int	`8`	(optional) number of velocity field integrations
`--interp`	InterpolationType	`Nearest`	(optional) the velocity field interpolation method (Options: Nearest, Trilinear, Tricubic, Gaussian, GaussianLocalLinear, GaussianLocalQuadratic)

Output:

Flag	Type	Description
`--velocity`	Volume	(optional) output forward deformation
`--forward`	Deformation	(optional) output forward deformation
`--backward`	Deformation	(optional) output backward deformation

MaskDice

Binarize a mask to convert all labels to zero or one.

Input:

Flag	Type	Description
`--left`	Mask	input left mask
`--right`	Mask	input right mask

MaskDilate

Dilate a mask morphologically.

Input:

Flag	Type	Description
`--input`	Mask	input mask

Parameters:

Flag	Type	Default	Description
`--num`	int	`1`	(optional) the number of times to dilate the mask
`--element`	String	`cross`	(optional) specify an element: cross, cube, or sphere. you can also specify an optional size, e.g. cross(3)
`--outside`	flag		(optional) treat voxels outside mask as background

Output:

Flag	Type	Description
`--output`	Mask	output mask

MaskDistanceTransform

Compute a distance transform using pff’s fast algorithm

Input:

Flag	Type	Description
`--input`	Mask	the input mask

Parameters:

Flag	Type	Default	Description
`--signed`	flag		(optional) compute a signed transform

Output:

Flag	Type	Description
`--output`	Volume	the output distance transform

Citation: Felzenszwalb, P., & Huttenlocher, D. (2004). DistanceExtrinsic transforms of sampled functions. Cornell University.

MaskEdge

Detect the edges of a input mask

Input:

Flag	Type	Description
`--input`	Mask	input input

Parameters:

Flag	Type	Default	Description
`--binary`	flag		(optional) binarize the edges
`--full`	flag		(optional) use a full neighborhood

Output:

Flag	Type	Description
`--output`	Mask	output input

MaskErode

Erode a mask morphologically

Input:

Flag	Type	Description
`--input`	Mask	input mask

Parameters:

Flag	Type	Default	Description
`--num`	int	`1`	(optional) the number of iterations
`--outside`	flag		(optional) treat voxels outside mask as background
`--verbose`	flag		(optional) print messages

Output:

Flag	Type	Description
`--output`	Mask	output mask

MaskExtract

Extract specific labels from a mask

Input:

Flag	Type	Description
`--input`	Mask	input mask
`--lookup`	Table	(optional) input lookup table (must store the index and name of each label)

Parameters:

Flag	Type	Default	Description
`--label`	String	`1`	(optional) the label(s) to extract (comma delimited, e.g. 1,2,3 or lh-temporal,rh-temporal if a lookup is used)
`--mode`	MaskExtractMode	`Binary`	(optional) the mode for extracting labels (Options: Binary, Preserve, Distinct)
`--name`	String	`name`	(optional) the name field in the lookup table
`--index`	String	`index`	(optional) the index field in the lookup table

Output:

Flag	Type	Description
`--output`	Mask	output mask

MaskFill

Flood fill the interior of the mask regions

Input:

Flag	Type	Description
`--input`	Mask	input mask

Output:

Flag	Type	Description
`--output`	Mask	output mask

MaskFilter

Filter a mask in a variety of possible ways

Input:

Flag	Type	Description
`--input`	Mask	input mask
`--mask`	Mask	(optional) a region to limit the filtering
`--ref`	Volume	(optional) input reference volume

Parameters:

Flag	Type	Description
`--mode`	flag	(optional) apply a mode filter
`--largest`	flag	(optional) extract the largest region
`--largestn`	Integer	(optional) extract the largest N region
`--minvox`	Integer	(optional) the minima region voxel count
`--minvol`	Double	(optional) the minima region volume
`--highest`	flag	(optional) extract the region with the highest average average reference value
`--lowest`	flag	(optional) extract the region with the lowest average average reference value
`--most`	flag	(optional) extract the region with the most total reference signal
`--binarize`	flag	(optional) binarize the mask at the end

Output:

Flag	Type	Description
`--output`	Mask	output mask

MaskFilterMedian

Perform median filtering of a mask.

Input:

Flag	Type	Description
`--input`	Mask	input volume
`--mask`	Mask	(optional) input mask

Parameters:

Flag	Type	Default	Description
`--window`	int	`1`	(optional) the window size in voxels
`--slice`	String		(optional) restrict the filtering to a specific slice (i, j, or k)
`--num`	Integer	`1`	(optional) the number of times to filter
`--threads`	Integer	`1`	(optional) the number of threads in the pool

Output:

Flag	Type	Description
`--output`	Mask	output volume

MaskFilterMode

Perform mode filtering a mask. Each voxel will be replaced by the most frequent label in the surrounding neighborhood, so this is like performing non-linear smoothing a mask

Input:

Flag	Type	Description
`--input`	Mask	input mask
`--mask`	Mask	(optional) input mask to restrict filtering

Parameters:

Flag	Type	Default	Description
`--radius`	int	`1`	(optional) the radius in voxels

Output:

Flag	Type	Description
`--output`	Mask	output mask

MaskForce

Compute a force field of a mask

Input:

Flag	Type	Description
`--input`	Mask	input mask
`--lookup`	Table	(optional) input lookup table (must store the index and name of each label)

Parameters:

Flag	Type	Default	Description
`--outside`	flag		(optional) only include forces outside
`--flip`	flag		(optional) flip the orientation of the forces
`--smooth`	flag		(optional) apply fiber smoothing after projection
`--which`	String		(optional) only process certain parcellation labels (by default all will be processed)
`--threads`	int	`1`	(optional) the number of threads

Advanced Parameters:

Flag	Type	Default	Description
`--range`	Double	`2.0`	(optional) the distance for the force field
`--sigma`	Double		(optional) apply smoothing with the given amount (bandwidth in mm) (default is largest voxel dimension)
`--support`	int	`3`	(optional) the smoothing filter radius in voxels
`--name`	String	`name`	(optional) the name field in the lookup table
`--index`	String	`index`	(optional) the index field in the lookup table

Output:

Flag	Type	Description
`--output`	Volume	the output vectors
`--labels`	Mask	(optional) the output mask of labels

MaskGreater

Extract the larger components of a mesh

Input:

Flag	Type	Description
`--input`	Mask	input mask

Parameters:

Flag	Type	Default	Description
`--minimum`	double	`25.0`	(optional) the minima volume

Output:

Flag	Type	Description
`--output`	Mask	output mask

MaskHull

Compute the convex hull of a mask

Input:

Flag	Type	Description
`--input`	Mask	input mask

Output:

Flag	Type	Description
`--output`	Mask	output mask

Citation: Barber, C. B., Dobkin, D. P., & Huhdanpaa, H. (1996). The quickhull algorithm for convex hulls. ACM Transactions on Mathematical Software (TOMS), 22(4), 469-483.

MaskIntersection

Compute the logical AND of two masks

Input:

Flag	Type	Description
`--left`	Mask	input left mask
`--right`	Mask	input right mask

Parameters:

Flag	Type	Default	Description
`--mode`	MaskIntersectionMode	`Left`	(optional) specify what label should be returned (Options: Left, Right, Max, Min, Sum, Product, One)

Output:

Flag	Type	Description
`--output`	Mask	output mask

MaskInvert

Invert the labels of a mask

Input:

Flag	Type	Description
`--input`	Mask	input mask
`--mask`	Mask	(optional) only invert in this region

Output:

Flag	Type	Description
`--output`	Mask	output mask

MaskLargest

Extract the largest component of a mask

Input:

Flag	Type	Description
`--input`	Mask	input mask

Output:

Flag	Type	Description
`--output`	Mask	output mask

MaskLateralize

Compute the logical AND of two masks

Input:

Flag	Type	Description
`--input`	Mask	input mask
`--left`	Mask	a mask marking off the left hemisphere (the remainder is assumed to be the right)

Parameters:

Flag	Type	Default	Description
`--leftPrefix`	String	`Left_`	(optional) the left prefix
`--leftPostfix`	String	``	(optional) the left postfix
`--rightPrefix`	String	`Right_`	(optional) the right prefix
`--rightPostfix`	String	``	(optional) the right postfix

Output:

Flag	Type	Description
`--output`	Mask	output mask

MaskLesser

Extract the smaller components of a mesh

Input:

Flag	Type	Description
`--input`	Mask	input mask

Parameters:

Flag	Type	Default	Description
`--maximum`	double	`25.0`	(optional) the maxima volume

Output:

Flag	Type	Description
`--output`	Mask	output mask

MaskList

Create a list of regions from a mask

Input:

Flag	Type	Description
`--input`	Mask	input mask
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--zero`	flag		(optional) include zero
`--base`	String	`region`	(optional) specify a basename
`--name`	String	`name`	(optional) specify the lookup name field
`--index`	String	`index`	(optional) specify the output index name

Output:

Flag	Type	Description
`--output`	Table	output table

MaskMRFEM

Refine a segmentation using a Expectation Maximization Markov Random Field framework

Input:

Flag	Type	Description
`--input`	Mask	input region
`--volume`	Volume	input volume
`--mask`	Mask	input mask

Parameters:

Flag	Type	Default	Description
`--distance`	Double	`1.0`	(optional) the distance in voxels for adaptation
`--mrfCross`	flag		(optional) use a 6-neighborhood (instead of a full 27-neighborhood with diagonals)
`--mrfGamma`	Double	`1.0`	(optional) use the following spatial regularization weight
`--mrfCrfGain`	Double	`1.0`	(optional) use the gain used for the conditional random field (zero will disable it)
`--mrfIcmIters`	Integer	`5`	(optional) use the following number of MRF optimization iterations
`--mrfEmIters`	Integer	`5`	(optional) use the following number of expectation maximization iteration

Output:

Flag	Type	Description
`--output`	Mask	output input

MaskMarchingCubes

Extract surfaces from a mask. If there are multiple labels in the volume, distinct meshes will be produced for each label.

Input:

Flag	Type	Description
`--input`	Mask	input mask
`--table`	Table	(optional) a table listing a subset of indices

Parameters:

Flag	Type	Default	Description
`--std`	Double		(optional) perform Gaussian smoothing before surface extraction
`--support`	Integer	`3`	(optional) use a given support in voxels for smoothing
`--level`	Double	`0.5`	(optional) use a given isolevel for smoothed surface extraction
`--which`	String		(optional) a string specifying a subset of labels, e.g. 1,2,4:6
`--meanarea`	Double		(optional) simplify the mesh to have the given mean triangle area

Advanced Parameters:

Flag	Type	Default	Description
`--tindex`	String	`index`	(optional) the index field name to use in the table
`--mindex`	String	`label`	(optional) the mesh attribute for the index value (default is “label”)

Output:

Flag	Type	Description
`--output`	Mesh	output mesh

Citation: Lorensen, W. E., & Cline, H. E. (1987, August). Marching cubes: A high resolution 3D surface construction algorithm. In ACM siggraph computer graphics (Vol. 21, No. 4, pp. 163-169). ACM.

MaskMarchingSquares

Extract contours from slices of a mask

Input:

Flag	Type	Description
`--input`	Mask	input mask

Parameters:

Flag	Type	Default	Description
`--dim`	String	`z`	(optional) volume channel to contour (x, y, or z)
`--start`	int	`0`	(optional) starting slice index
`--step`	int	`1`	(optional) number of slices between contours

Output:

Flag	Type	Description
`--output`	Curves	output curves

Citation: Maple, C. (2003, July). Geometric design and space planning using the marching squares and marching cube algorithms. In Geometric Modeling and Graphics, 2003. Proceedings. 2003 International Conference on (pp. 90-95). IEEE.

MaskMatch

Match the dimensions of a mask to a reference image. For example, if you draw a mask on downsampled version of an image, this will upsample the labels to match the high resolution original image.

Input:

Flag	Type	Description
`--input`	Mask	input mask
`--reference`	Volume	input reference image

Output:

Flag	Type	Description
`--output`	Mask	output mask

MaskMeasure

Measure properties of a mask

Input:

Flag	Type	Description
`--input`	Mask	input mask
`--region`	Mask	(optional) restrict the analysis to a given region of interest
`--lookup`	Table	(optional) use a lookup for region names

Parameters:

Flag	Type	Default	Description
`--nameField`	String	`name`	(optional) specify the output name field
`--valueField`	String	`value`	(optional) specify the output value field name
`--lutNameField`	String	`name`	(optional) specify the lookup name field
`--lutIndexField`	String	`index`	(optional) specify the lut index field name
`--volumes`	flag		(optional) report only the region volumes
`--fraction`	flag		(optional) compute the fraction of each region
`--cluster`	flag		(optional) compute cluster statistics of each region
`--position`	flag		(optional) compute the position of each region
`--components`	flag		(optional) run connected components labeling before anything else
`--binarize`	flag		(optional) binarize the mask before anything else (overrides the components flag)
`--comps`	flag		(optional) include component counts in the report
`--counts`	flag		(optional) include voxel counts in the report
`--minvolume`	Double		(optional) the minimum component volume (mm^3) to be included
`--minvoxels`	Integer		(optional) the minimum component voxel count to be included

Output:

Flag	Type	Description
`--output`	Table	output table

MaskMeasureClusters

Measure individual cluster sizes of a mask

Input:

Flag	Type	Description
`--input`	Mask	input mask
`--region`	Mask	(optional) restrict the analysis to a given region of interest
`--lookup`	Table	(optional) use a lookup for region names

Parameters:

Flag	Type	Default	Description
`--nameField`	String	`name`	(optional) specify the output name field
`--clusterField`	String	`cluster`	(optional) specify the output cluster field
`--voxelsField`	String	`voxels`	(optional) specify the output voxel count field name
`--lutNameField`	String	`name`	(optional) specify the lookup name field
`--lutIndexField`	String	`index`	(optional) specify the lut index field name
`--minvolume`	Double		(optional) the minimum component volume (mm^3) to be included
`--minvoxels`	Integer		(optional) the minimum component voxel count to be included

Output:

Flag	Type	Description
`--output`	Table	output table

MaskMirror

Mirror a mask is the given direction

Input:

Flag	Type	Description
`--input`	Mask	input mask

Parameters:

Flag	Type	Description
`--flipi`	flag	(optional) flip in i
`--flipj`	flag	(optional) flip in j
`--flipk`	flag	(optional) flip in k

Output:

Flag	Type	Description
`--output`	Mask	output mask

MaskNodeLink

Create a node link representation of mask connectivity in a mesh

Input:

Flag	Type	Description
`--input`	Mask	input mask
`--lookup`	Table	input table
`--attributes`	Table	input attributes

Parameters:

Flag	Type	Default	Description
`--index`	String	`index`	(optional) index
`--name`	String	`name`	(optional) name
`--group`	String	`group`	(optional) group
`--value`	String	`value`	(optional) value
`--radius`	double	`10.0`	(optional) radius
`--subdiv`	int	`2`	(optional) subdiv

Output:

Flag	Type	Description
`--links`	Curves	(optional) output links
`--nodes`	Mesh	(optional) output nodes

MaskOpen

Open a mask using morphological operations. This first erodes the mask and then dilates it.

Input:

Flag	Type	Description
`--input`	Mask	input mask

Parameters:

Flag	Type	Default	Description
`--num`	int	`1`	(optional) the number of times to erode and dilate the mask
`--largest`	flag		(optional) select the largest component as an intermediate step between erosion and dilation
`--mode`	flag		(optional) apply a mode filter as an intermediate step between erosion and dilation
`--element`	String	`cross`	(optional) specify an element: cross, cube, or sphere. you can also specify an optional size, e.g. cross(3)
`--outside`	flag		(optional) treat voxels outside mask as background

Output:

Flag	Type	Description
`--output`	Mask	output mask

MaskOrigin

Set the origin of a mask

Input:

Flag	Type	Description
`--input`	Mask	the input Mask

Parameters:

Flag	Type	Default	Description
`--x`	double	`0.0`	(optional) the origin in x
`--y`	double	`0.0`	(optional) the origin in y
`--z`	double	`0.0`	(optional) the origin in z

Output:

Flag	Type	Description
`--output`	Mask	the output Mask

MaskPad

Pad a mask by a given number of voxels

Input:

Flag	Type	Description
`--input`	Mask	input mask

Parameters:

Flag	Type	Default	Description
`--pad`	int	`10`	(optional) the amount of padding in voxels

Output:

Flag	Type	Description
`--output`	Mask	output mask

MaskPhantomNoisy

Generate a noisy mask

Parameters:

Flag	Type	Default	Description
`--width`	int	`100`	(optional) image width
`--height`	int	`100`	(optional) image height
`--slices`	int	`1`	(optional) image slices
`--labels`	int	`1`	(optional) the number of labels to use

Output:

Flag	Type	Description
`--output`	Mask	output mask

MaskPrintInfo

Print basic information about a mask

Input:

Flag	Type	Description
`--input`	Mask	the input mask

Parameters:

Flag	Type	Default	Description
`--stats`	flag		(optional) print statistics

MaskProduct

Compute the product of two multi-label masks. Unlike MaskIntersection, this will make sure the product is unique and the names are updated.

Input:

Flag	Type	Description
`--left`	Mask	input left mask
`--right`	Mask	input right mask

Parameters:

Flag	Type	Default	Description
`--sep`	String	`_`	(optional) the string for combining region names

Output:

Flag	Type	Description
`--output`	Mask	output mask

MaskPrototype

Create a mask from example data

Input:

Flag	Type	Description
`--mask`	Mask	(optional) an example mask
`--volume`	Volume	(optional) an example volume

Parameters:

Flag	Type	Default	Description
`--label`	int	`0`	(optional) the default label

Output:

Flag	Type	Description
`--output`	Mask	output

MaskRegionMerge

Merge small regions using an adjacency graph

Input:

Flag	Type	Description
`--input`	Mask	input region input

Parameters:

Flag	Type	Default	Description
`--threshold`	double	`10.0`	(optional) the input threshold
`--full`	flag		(optional) use a full 27-voxel neighborhood (default is 6-voxel)

Output:

Flag	Type	Description
`--output`	Mask	output input

MaskRelabel

Relabel a mask by replacing voxel labels with new values

Input:

Flag	Type	Description
`--mask`	Mask	input mask
`--mapping`	Table	input mapping (includes fields named ‘from’ and ‘to’)
`--lookup`	Table	(optional) input lookup

Parameters:

Flag	Type	Default	Description
`--preserve`	flag		(optional) preserve the input labels if possible
`--names`	flag		(optional) use names for remapping (instead of index labels)
`--from`	String	`from`	(optional) specify a from field to us in mapping
`--to`	String	`to`	(optional) specify a to field to us in mapping
`--name`	String	`name`	(optional) the name field
`--index`	String	`index`	(optional) the index field

Output:

Flag	Type	Description
`--outputMask`	Mask	output mask
`--outputLookup`	Table	(optional) output lookup

MaskReorder

Change the ordering of voxels in a mask. You can flip and shift the voxels. Which shifting outside the field a view, the data is wrapped around. Shifting is applied before flipping

Input:

Flag	Type	Description
`--input`	Mask	input mask

Parameters:

Flag	Type	Default	Description
`--flipi`	flag		(optional) flip in i
`--flipj`	flag		(optional) flip in j
`--flipk`	flag		(optional) flip in k
`--shifti`	int	`0`	(optional) shift in i
`--shiftj`	int	`0`	(optional) shift in j
`--shiftk`	int	`0`	(optional) shift in k

Output:

Flag	Type	Description
`--output`	Mask	output mask

MaskResample

Resample a mask with a different voxel size

Input:

Flag	Type	Description
`--input`	Mask	the input volume

Parameters:

Flag	Type	Default	Description
`--dx`	double	`1.0`	(optional) the voxel size in x
`--dy`	double	`1.0`	(optional) the voxel size in y
`--dz`	double	`1.0`	(optional) the voxel size in z

Output:

Flag	Type	Description
`--output`	Mask	the output volume

MaskRestoreMRF

Restore a mask using a markov random field with loopy belief propagation

Input:

Flag	Type	Description
`--input`	Mask	input mask
`--mask`	Mask	(optional) a mask of the area to restore

Parameters:

Flag	Type	Default	Description
`--cost`	double	`0.75`	(optional) the cost for changing a voxel label
`--data`	double	`1.0`	(optional) the weight for the data term
`--smooth`	double	`1.0`	(optional) the weight for the smoothness term
`--iters`	int	`50`	(optional) the number of belief propagation iterations

Output:

Flag	Type	Description
`--output`	Mask	output mask

Citation: Felzenszwalb, P. F., & Huttenlocher, D. P. (2006). Efficient belief propagation for early vision. International journal of computer vision, 70(1), 41-54.

MaskRings

Compute equidistant rings around a region

Input:

Flag	Type	Description
`--input`	Mask	input region
`--mask`	Mask	(optional) input mask

Parameters:

Flag	Type	Default	Description
`--levels`	String	`3,5,7,9`	(optional) the levels for segmentation (comma-separated in mm)

Output:

Flag	Type	Description
`--output`	Mask	output mask

MaskSampleVects

Sample vects from a mask

Input:

Flag	Type	Description
`--input`	Mask	input mask

Parameters:

Flag	Type	Default	Description
`--count`	int	`1`	(optional) the number of samples per voxel
`--limit`	int	`10000`	(optional) the maximum number of points to produce

Output:

Flag	Type	Description
`--output`	Vects	output vects

MaskSet

Set the values of a mask

Input:

Flag	Type	Description
`--input`	Mask	the input mask
`--solids`	Solids	(optional) some solids
`--vects`	Vects	(optional) some vects
`--mask`	Mask	(optional) the mask

Parameters:

Flag	Type	Default	Description
`--clear`	flag		(optional) clear the input labels before setting anything
`--range`	String		(optional) a range, e.g. start:end,start:end,start:end
`--label`	int	`1`	(optional) the label to set

Output:

Flag	Type	Description
`--output`	Mask	the output mask

MaskSetEyes

Binarize a mask to convert all labels to zero or one.

Input:

Flag	Type	Description
`--input`	Mask	input reference mask
`--eyes`	Vects	input eye positions

Parameters:

Flag	Type	Default	Description
`--start`	double	`10.0`	(optional) the starting level
`--end`	double	`55.0`	(optional) the end level

Output:

Flag	Type	Description
`--output`	Mask	output mask

MaskSetTable

Create a table listing regions of a mask

Input:

Flag	Type	Description
`--reference`	Mask	input reference
`--table`	Table	input table
`--lookup`	Table	(optional) a lookup table to relate names to indices

Parameters:

Flag	Type	Default	Description
`--merge`	String	`name`	(optional) a field name to merge on
`--index`	String	`index`	(optional) the index field name
`--value`	String	`value`	(optional) a field to set
`--background`	double	`0.0`	(optional) a background value
`--missing`	Double		(optional) an missing value

Output:

Flag	Type	Description
`--output`	Volume	output volume

MaskShell

Compute the shell of a mask (the voxels at the boundary of the mesh)

Input:

Flag	Type	Description
`--input`	Mask	input mask

Parameters:

Flag	Type	Default	Description
`--num`	int	`1`	(optional) dilate this many times
`--mode`	ShellMode	`Inner`	(optional) specify a mode for computing the shell (Options: Inner, Outer, Multi)

Output:

Flag	Type	Description
`--output`	Mask	output mask

MaskSkeleton

Skeletonize a mask using medial axis thinning. Based on Hanno Homan’s implementation of Lee et al. at http://hdl.handle.net/1926/1292

Input:

Flag	Type	Description
`--input`	Mask	input mask

Output:

Flag	Type	Description
`--output`	Mask	output mask

Citation: Lee, Ta-Chih, Rangasami L. Kashyap, and Chong-Nam Chu. Building skeleton models via 3-D medial surface axis thinning algorithms. CVGIP: Graphical Models and Image Processing 56.6 (1994): 462-478.

MaskSort

Sort the labels of a mask by their size

Input:

Flag	Type	Description
`--input`	Mask	input mask

Output:

Flag	Type	Description
`--output`	Mask	output mask

MaskSplitMidline

Split mask regions at the midline to produce left and right regions

Input:

Flag	Type	Description
`--mask`	Mask	input mask
`--lookup`	Table	(optional) input lookup

Parameters:

Flag	Type	Default	Description
`--pattern`	String	`%{hemi}_%{name}`	(optional) a pattern for renaming entries
`--midline`	Integer		(optional) specify a midline index (otherwise the middle is used)
`--start`	Integer	`1`	(optional) specify an offset value (0 or 1)
`--left`	String	`left`	(optional) specify an identifier for the left hemisphere
`--right`	String	`right`	(optional) specify an identifier for the right hemisphere
`--name`	String	`name`	(optional) the name field in the lookup table
`--index`	String	`index`	(optional) the index field in the lookup table

Output:

Flag	Type	Description
`--outputMask`	Mask	output mask
`--outputLookup`	Table	(optional) output lookup

MaskStandardize

Standardize the pose of a mask

Input:

Flag	Type	Description
`--input`	Mask	input mask

Output:

Flag	Type	Description
`--output`	Mask	(optional) output mask
`--xfm`	Affine	(optional) output affine
`--invxfm`	Affine	(optional) output inverse affine

MaskSymmetrize

Make a left/right pair masks symmetric

Input:

Flag	Type	Description
`--inputLeft`	Mask	input left mask
`--inputRight`	Mask	input right mask

Output:

Flag	Type	Description
`--outputLeft`	Mask	output left mask
`--outputRight`	Mask	output right mask

MaskTable

Create a table listing regions of a mask

Input:

Flag	Type	Description
`--input`	Mask	input mask

Parameters:

Flag	Type	Default	Description
`--nameField`	String	`name`	(optional) the region name field
`--indexField`	String	`index`	(optional) the region label field
`--namePattern`	String	`region%d`	(optional) a pattern for naming regions
`--xField`	String	`x`	(optional) the region centroid x field
`--yField`	String	`y`	(optional) the region centroid y field
`--zField`	String	`z`	(optional) the region centroid z field
`--name`	flag		(optional) include a name field
`--centroid`	flag		(optional) include a centroid fields

Output:

Flag	Type	Description
`--output`	Table	output table

MaskThick

Filter the mask to include only subregions with at least the given thickness

Input:

Flag	Type	Description
`--input`	Mask	input mask

Parameters:

Flag	Type	Default	Description
`--num`	int	`1`	(optional) the minimum thickness in voxels
`--element`	String	`cross`	(optional) specify an element: cross, cube, or sphere. you can also specify an optional size, e.g. cross(3)

Output:

Flag	Type	Description
`--output`	Mask	output mask

MaskTransform

Transform a mask

Input:

Flag	Type	Description
`--input`	Mask	input volume
`--reference`	Volume	input reference volume
`--mask`	Mask	(optional) input mask (defined in the reference space)
`--inputMask`	Mask	(optional) use an input mask (defined in the input space)
`--affine`	Affine	(optional) apply an affine xfm
`--invaffine`	Affine	(optional) apply an inverse affine xfm
`--deform`	Deformation	(optional) apply a deformation xfm

Parameters:

Flag	Type	Default	Description
`--reverse`	flag		(optional) reverse the order, i.e. compose the affine(deform(x)), whereas the default is deform(affine(x))
`--background`	Integer		(optional) a label for filling background voxels

Output:

Flag	Type	Description
`--output`	Mask	output volume

MaskUnion

Combine two masks into one. By default, the left mask labels will be preserved and background voxels will be OR-ed with the right mask. You can optionally relabel the result to assign new labels to distinct pairs of left/right labels

Input:

Flag	Type	Description
`--left`	Mask	input left mask
`--right`	Mask	input right mask

Parameters:

Flag	Type	Description
`--relabel`	flag	(optional) combine the masks using distinct values
`--max`	flag	(optional) use the maximum label when masks overlap (default is to use the left)
`--distinct`	flag	(optional) use a label of one for the left mask and a label of two for the right

Output:

Flag	Type	Description
`--output`	Mask	output mask

MaskVects

Extract a vector for each foreground voxel

Input:

Flag	Type	Description
`--input`	Mask	input mask

Output:

Flag	Type	Description
`--output`	Vects	output vects

MaskZoom

Zoom a mask

Input:

Flag	Type	Description
`--input`	Mask	input mask

Parameters:

Flag	Type	Default	Description
`--factor`	Double	`2.0`	(optional) an isotropic scaling factor
`--isotropic`	Double		(optional) an isotropic scaling factor
`--fi`	Double		(optional) a scaling factor in i
`--fj`	Double		(optional) a scaling factor in j
`--fk`	Double		(optional) a scaling factor in k
`--mode`	flag		(optional) filter the mask to smooth it

Output:

Flag	Type	Description
`--output`	Mask	output mask

MatrixConvert

Convert a matrix between file formats

Input:

Flag	Type	Description
`--input`	Matrix	input matrix

Output:

Flag	Type	Description
`--output`	Matrix	output matrix

MatrixCreate

Create a matrix

Parameters:

Flag	Type	Default	Description
`--identity`	Integer		create an identity matrix with the given channel

Output:

Flag	Type	Description
`--output`	Matrix	output matrix

MatrixInvert

Invert a matrix

Input:

Flag	Type	Description
`--input`	Matrix	input matrix

Output:

Flag	Type	Description
`--output`	Matrix	output matrix

MatrixOrthogonalize

Orthogonalize a matrix

Input:

Flag	Type	Description
`--input`	Matrix	input matrix

Output:

Flag	Type	Description
`--output`	Matrix	output matrix

MatrixPrintInfo

Print basic information about a matrix

Input:

Flag	Type	Description
`--input`	Matrix	the input matrix

MatrixTranspose

Transpose a matrix

Input:

Flag	Type	Description
`--input`	Matrix	input matrix

Output:

Flag	Type	Description
`--output`	Matrix	output matrix

MeshAttrBoundary

Extract the boundaries of mesh regions

Input:

Flag	Type	Description
`--input`	Mesh	the input Mesh

Parameters:

Flag	Type	Default	Description
`--coord`	String	`coord`	(optional) a comma-separated list of coordinate attributes to lift
`--label`	String	`coord`	(optional) the label attribute name
`--threshold`	double	`0.5`	(optional) use a given threshold for picking the boundary
`--lift`	double	`0.0`	(optional) apply the given amount of lift off the mesh

Output:

Flag	Type	Description
`--output`	Mesh	the output Mesh

MeshAttrClose

Close a mesh vertex selection

Input:

Flag	Type	Description
`--input`	Mesh	input mesh

Parameters:

Flag	Type	Default	Description
`--largest`	flag		(optional) select the largest component as an intermediate step
`--num`	int	`1`	(optional) the number of iterations
`--attrin`	String	`selection`	(optional) the input attribute
`--attrout`	String		(optional) the output attribute

Output:

Flag	Type	Description
`--output`	Mesh	output mesh

MeshAttrComponents

Compute connected components of a mesh selection

Input:

Flag	Type	Description
`--input`	Mesh	the input mesh

Parameters:

Flag	Type	Default	Description
`--largest`	flag		(optional) retain only the largest component
`--attrin`	String	`selection`	(optional) the input attribute
`--attrout`	String		(optional) the output attribute

Output:

Flag	Type	Description
`--output`	Mesh	the output mesh

MeshAttrCortexToVolume

Project cortical surface data to a volume

Input:

Flag	Type	Description
`--input`	Mesh	input mesh
`--refvolume`	Volume	(optional) input reference volume (exclusive with refmask)
`--refmask`	Mask	(optional) input reference mask (exclusive with refvolume)

Parameters:

Flag	Type	Default	Description
`--pial`	String	`pial`	(optional) pial attribute name
`--white`	String	`white`	(optional) white attribute name
`--attr`	String	`thickness`	(optional) the attribute to project
`--mindist`	double	`1.0`	(optional) the minimum white-pial to be included
`--samples`	int	`15`	(optional) the number of points to sample
`--inner`	double	`0.0`	(optional) the inner buffer size
`--outer`	double	`0.0`	(optional) the outer buffer size
`--smooth`	flag		(optional) apply fiber smoothing after projection
`--nofill`	flag		(optional) skip the filling step
`--threads`	int	`1`	(optional) the number of threads

Advanced Parameters:

Flag	Type	Default	Description
`--sigma`	Double		(optional) apply smoothing with the given amount (bandwidth in mm) (default is largest voxel dimension)
`--support`	int	`3`	(optional) the smoothing filter radius in voxels

Output:

Flag	Type	Description
`--output`	Volume	the output projection

MeshAttrCrop

Crop a mesh from a selection

Input:

Flag	Type	Description
`--input`	Mesh	the input mesh

Parameters:

Flag	Type	Default	Description
`--invert`	flag		(optional) invert the selection
`--attr`	String	`selection`	(optional) the selection attribute

Output:

Flag	Type	Description
`--output`	Mesh	the output mesh

MeshAttrDilate

Dilate a mesh selection

Input:

Flag	Type	Description
`--input`	Mesh	input mesh

Parameters:

Flag	Type	Default	Description
`--num`	int	`1`	(optional) the number of iterations
`--attrin`	String	`selection`	(optional) the input attribute
`--attrout`	String		(optional) the output attribute

Output:

Flag	Type	Description
`--output`	Mesh	output mesh

MeshAttrErode

Erode a mesh selection

Input:

Flag	Type	Description
`--input`	Mesh	input mesh

Parameters:

Flag	Type	Default	Description
`--num`	int	`1`	(optional) the number of iterations
`--attrin`	String	`selection`	(optional) the input attribute
`--attrout`	String		(optional) the output attribute

Output:

Flag	Type	Description
`--output`	Mesh	output mesh

MeshAttrGetTable

Create a table from mesh vertex attributes

Input:

Flag	Type	Description
`--input`	Mesh	input input

Parameters:

Flag	Type	Default	Description
`--vertices`	String		(optional) which vertices retain (comma separated)
`--which`	String	`coord`	(optional) which attributes to retain (comma separated)

Output:

Flag	Type	Description
`--output`	Table	output table

MeshAttrGetVects

Extract a mesh vertex attribute as vectors

Input:

Flag	Type	Description
`--input`	Mesh	input mesh

Parameters:

Flag	Type	Default	Description
`--attr`	String	`attr`	(optional) the destination attribute name

Output:

Flag	Type	Description
`--output`	Vects	output mesh

MeshAttrLaplacian

Filter a mesh with a laplacian

Input:

Flag	Type	Description
`--input`	Mesh	the input

Parameters:

Flag	Type	Default	Description
`--attrin`	String	`coord`	(optional) the input attribute to filter
`--attrout`	String		(optional) the output attribute names (if none, the input is replaced)
`--num`	int	`5`	(optional) a number of iterations
`--lambda`	Double	`0.3`	(optional) the lambda laplacian filtering parameter

Output:

Flag	Type	Description
`--output`	Mesh	the output mesh

MeshAttrMask

Apply a mask to an attribute

Input:

Flag	Type	Description
`--input`	Mesh	input mesh

Parameters:

Flag	Type	Default	Description
`--mask`	String	`mask`	(optional) the mask attribute
`--attrin`	String	`selection`	(optional) the input attribute
`--attrout`	String		(optional) the output attribute

Output:

Flag	Type	Description
`--output`	Mesh	output mesh

MeshAttrMath

Evaluate an expression at each vertex of a mesh

Input:

Flag	Type	Description
`--input`	Mesh	the input mesh

Parameters:

Flag	Type	Default	Description
`--expression`	String	`x > 0.5`	(optional) the expression to evaluate
`--result`	String	`result`	(optional) the attribute for the result

Output:

Flag	Type	Description
`--output`	Mesh	the output mesh

MeshAttrMeasure

Measure regional attributes properties of a mesh

Input:

Flag	Type	Description
`--input`	Mesh	input mesh
`--labels`	Vects	(optional) add a pacellation attribute
`--lookup`	Table	(optional) use a lookup table for naming regions

Parameters:

Flag	Type	Default	Description
`--attr`	String		compute statistics of the following numerical attributes (a comma-delimited list can be used)
`--output`	String		output directory
`--label`	String	`label`	(optional) the name of the parcellation attribute
`--binary`	flag		(optional) treat the parcellation as binary (zero vs. non-zero)
`--lutname`	String	`name`	(optional) the lookup table name field
`--lutindex`	String	`index`	(optional) the lookup table index field
`--outname`	String	`name`	(optional) the output table name field
`--outvalue`	String	`value`	(optional) the output table value field

MeshAttrMeasureBinary

Measure regional attributes properties of a mesh with a binary labelling

Input:

Flag	Type	Description
`--input`	Mesh	input mesh
`--labels`	Vects	(optional) add a parcellation attribute

Parameters:

Flag	Type	Default	Description
`--attr`	String		(optional) compute statistics of the following numerical attributes (a comma-delimited list can be used)
`--label`	String	`label`	(optional) the name of the parcellation attribute
`--whole`	String	`whole`	(optional) the name of the whole attribute
`--prefix`	String	``	(optional) a prefix for naming
`--coord`	String	`coord`	(optional) the coordinate field (comma-separate list too)
`--outname`	String	`name`	(optional) the output table name field
`--outvalue`	String	`value`	(optional) the output table value field

Output:

Flag	Type	Description
`--output`	Table	output table

MeshAttrMedian

Smooth a mesh with a median filter

Input:

Flag	Type	Description
`--input`	Mesh	the input

Parameters:

Flag	Type	Default	Description
`--attrin`	String	`coord`	(optional) the attribute to smooth
`--attrout`	String		(optional) the output attribute names (if none, the input is replaced)
`--num`	int	`5`	(optional) a number of iterations

Output:

Flag	Type	Description
`--output`	Mesh	the output mesh

MeshAttrMode

Filter a mesh attribute with a mode filter

Input:

Flag	Type	Description
`--input`	Mesh	the input

Parameters:

Flag	Type	Default	Description
`--attrin`	String	`coord`	(optional) the attribute to smooth
`--attrout`	String		(optional) the output attribute names (if none, the input is replaced)
`--num`	int	`5`	(optional) a number of iterations

Output:

Flag	Type	Description
`--output`	Mesh	the output mesh

MeshAttrOpen

Open a mesh selection

Input:

Flag	Type	Description
`--input`	Mesh	input mesh

Parameters:

Flag	Type	Default	Description
`--largest`	flag		(optional) select the largest component as an intermediate step
`--num`	int	`1`	(optional) the number of iterations
`--attrin`	String	`selection`	(optional) the input attribute
`--attrout`	String		(optional) the output attribute

Output:

Flag	Type	Description
`--output`	Mesh	output mesh

MeshAttrParcel

Extract and measure a parcel

Input:

Flag	Type	Description
`--input`	Mesh	the input Mesh
`--prior`	Vects	the input prior attribute vectors
`--whole`	Vects	(optional) the input whole surface attribute vectors

Parameters:

Flag	Type	Default	Description
`--coord`	String	`coord`	(optional) a comma-separated list of coordinate attributes
`--name`	String	`parcel`	(optional) the parcel name
`--measure`	String		(optional) the attributes to measure (comma-separated)
`--segment`	String	`segment`	(optional) the attribute for segmentation
`--threshold`	double	`0.5`	(optional) the value for thresholding
`--invert`	flag		(optional) apply an inverse threshold
`--normalize`	flag		(optional) normalize the segmentation attribute (scale based on either the mode or mean)
`--stat`	MeshAttrParcelStat	`Mean`	(optional) the statistic to use for normalization (Options: Mode, Mean)
`--otsu`	flag		(optional) use an Otsu threshold (the specific threshold is ignored)
`--bins`	int	`512`	(optional) the number of bins for Otsu thresholding
`--smooth`	int	`2`	(optional) the number of smoothing operations
`--mode`	int	`2`	(optional) the number of mode filters

Output:

Flag	Type	Description
`--outputMask`	Vects	the output segmentation mask
`--outputTable`	Table	the output statistics

MeshAttrSetTable

Create a table listing regions of a mask

Input:

Flag	Type	Description
`--mesh`	Mesh	input mesh
`--table`	Table	input table
`--lookup`	Table	(optional) a lookup table to relate names to indices

Parameters:

Flag	Type	Default	Description
`--merge`	String	`name`	(optional) a field name to merge on
`--index`	String	`index`	(optional) the table index field name
`--value`	String	`value`	(optional) a table field to get (can be comma delimited)
`--mindex`	String		(optional) the mesh index field name (defaults to table index field name)
`--mvalue`	String		(optional) the mesh value field name (defaults to table value field name)
`--background`	double	`0.0`	(optional) a background value
`--missing`	Double		(optional) an missing value
`--remove`	flag		(optional) remove triangles with vertices that are not included in the input table

Output:

Flag	Type	Description
`--output`	Mesh	output mesh

MeshAttrSetVects

Add vects as an attribute on a mesh (number of vects must match the number of vertices)

Input:

Flag	Type	Description
`--input`	Mesh	input mesh
`--vects`	Vects	input vects

Parameters:

Flag	Type	Default	Description
`--attr`	String	`attr`	(optional) the destination attribute name

Output:

Flag	Type	Description
`--output`	Mesh	output mesh

MeshAttrThreshold

Apply a threshold to a mesh attribute

Input:

Flag	Type	Description
`--input`	Mesh	the input

Parameters:

Flag	Type	Default	Description
`--attrin`	String	`coord`	(optional) the input attribute to threshold
`--attrout`	String		(optional) the output attribute names (if none, the input is replaced)
`--threshold`	Double	`0.5`	(optional) threshold value
`--magnitude`	flag		(optional) use the magnitude for multi-variate attribtues
`--invert`	flag		(optional) invert the threshold

Output:

Flag	Type	Description
`--output`	Mesh	the output mesh

MeshAttributes

Manipulate mesh vertex attributes. Operations support comma-delimited lists

Input:

Flag	Type	Description
`--input`	Mesh	the input Mesh

Parameters:

Flag	Type	Description
`--copy`	String	(optional) copy attribute (x=y syntax)
`--rename`	String	(optional) rename attribute (x=y syntax)
`--remove`	String	(optional) remove attribute (- for all)
`--retain`	String	(optional) retain the given attributes and remove others)

Output:

Flag	Type	Description
`--output`	Mesh	the output Mesh

MeshBox

Get the bounding box of a mesh

Input:

Flag	Type	Description
`--input`	Mesh	input mesh

Output:

Flag	Type	Description
`--output`	Solids	output box

MeshCat

Concatentate two meshes

Input:

Flag	Type	Description
`--left`	Mesh	input left
`--right`	Mesh	input right

Output:

Flag	Type	Description
`--output`	Mesh	output mesh

MeshComponents

Compute connected components of a mesh

Input:

Flag	Type	Description
`--input`	Mesh	the input mesh

Parameters:

Flag	Type	Default	Description
`--largest`	flag		(optional) retain only the largest component
`--attr`	String	`index`	(optional) the name of the component attribute
`--select`	String		(optional) retain components selected with the given attribute
`--area`	Double		(optional) retain components above a given surface area
`--invert`	flag		(optional) invert the selection

Output:

Flag	Type	Description
`--output`	Mesh	the output mesh

MeshConvert

Convert a mesh between file formats

Input:

Flag	Type	Description
`--input`	Mesh	input mesh

Output:

Flag	Type	Description
`--output`	Mesh	output mesh

MeshCreateBox

Create a box

Output:

Flag	Type	Description
`--output`	Mesh	output mesh

MeshCreateCylinder

Create a cylinder mesh

Parameters:

Flag	Type	Default	Description
`--startx`	double	`0.0`	(optional) input start x coordinate
`--starty`	double	`0.0`	(optional) input start y coordinate
`--startz`	double	`0.0`	(optional) input start z coordinate
`--endx`	double	`1.0`	(optional) input end x coordinate
`--endy`	double	`10.0`	(optional) input end y coordinate
`--endz`	double	`10.0`	(optional) input end z coordinate
`--radius`	double	`5.0`	(optional) input radius
`--resolution`	int	`5`	(optional) input resolution

Output:

Flag	Type	Description
`--output`	Mesh	output mesh

MeshCreateHemisphere

Create a hemisphere mesh

Parameters:

Flag	Type	Default	Description
`--sudiv`	int	`1`	(optional) the number of subdivisions

Output:

Flag	Type	Description
`--output`	Mesh	output mesh

MeshCreateIcosahedron

Create a icosahedron

Output:

Flag	Type	Description
`--output`	Mesh	output mesh

MeshCreateOctahedron

Create an octahedron

Output:

Flag	Type	Description
`--output`	Mesh	output mesh

MeshCreateSphere

Create a sphere mesh

Parameters:

Flag	Type	Default	Description
`--x`	double	`0.0`	(optional) input x coordinate
`--y`	double	`0.0`	(optional) input y coordinate
`--z`	double	`0.0`	(optional) input z coordinate
`--radius`	double	`5.0`	(optional) input radius
`--subdiv`	int	`2`	(optional) input subdivisions

Output:

Flag	Type	Description
`--output`	Mesh	output mesh

MeshCreateTetrahedron

Create a tetrahedron

Output:

Flag	Type	Description
`--output`	Mesh	output mesh

MeshCrop

Crop a mesh

Input:

Flag	Type	Description
`--input`	Mesh	the input mesh
`--solids`	Solids	(optional) remove vertices inside the given solids

Parameters:

Flag	Type	Default	Description
`--selection`	String		(optional) remove vertices that are selected with a non-zero attribute
`--invert`	flag		(optional) invert the selection

Output:

Flag	Type	Description
`--output`	Mesh	the output mesh

MeshExtract

Extract a subset of a mesh that matches the given attribute values

Input:

Flag	Type	Description
`--input`	Mesh	input mesh

Parameters:

Flag	Type	Default	Description
`--attr`	String	`label`	(optional) the attribute name of the label used to select
`--include`	String		(optional) which labels to include, e.g. 1,2,3:5
`--exclude`	String		(optional) which labels to exclude, e.g. 1,2,3:5

Output:

Flag	Type	Description
`--output`	Mesh	output mesh

MeshFeatures

Compute geometric features of a mesh at each vertex. A locally quadratic approximation at each vertex is used to find curvature features

Input:

Flag	Type	Description
`--input`	Mesh	the input mesh

Parameters:

Flag	Type	Default	Description
`--attr`	String	`coord`	(optional) the mesh attribute
`--rings`	int	`2`	(optional) the number of vertex rings to use for estimation
`--smooth`	int	`0`	(optional) the number of pre-smoothing iterations
`--refine`	flag		(optional) refine the vertex positions to match the quadratic estimate (a loess type filter)
`--step`	double	`0.001`	(optional) the gradient step size for refinement
`--thresh`	double	`0.01`	(optional) the error threshold for refinement
`--iters`	int	`1000`	(optional) the maximum number of refinement iterations
`--scaling`	double	`2.0`	(optional) the scaling factor for boundary estimation

Output:

Flag	Type	Description
`--output`	Mesh	the output mesh

MeshFeaturesCortex

Compute cortical surface features of a mesh at each vertex

Input:

Flag	Type	Description
`--input`	Mesh	the input mesh

Parameters:

Flag	Type	Default	Description
`--attr`	String	`coord`	(optional) the mesh attribute
`--outer`	String	`pial`	(optional) the outer pial mesh attribute
`--inner`	String	`white`	(optional) the inner mesh attribute

Output:

Flag	Type	Description
`--output`	Mesh	the output mesh

Citation: Winkler, A. M., Sabuncu, M. R., Yeo, B. T., Fischl, B., Greve, D. N., Kochunov, P., … & Glahn, D. C. (2012). Measuring and comparing brain cortical surface area and other areal quantities. Neuroimage, 61(4), 1428-1443.

MeshFlipNormals

Flip the normals of a mesh

Input:

Flag	Type	Description
`--input`	Mesh	the input mesh

Output:

Flag	Type	Description
`--output`	Mesh	the output mesh

MeshForceCortex

Compute the force field of a cortical mesh

Input:

Flag	Type	Description
`--input`	Mesh	input mesh
`--refvolume`	Volume	(optional) input reference volume (exclusive with refmask)
`--refmask`	Mask	(optional) input reference mask (exclusive with refvolume)
`--lookup`	Table	(optional) input lookup table (must store the index and name of each label)

Parameters:

Flag	Type	Default	Description
`--pial`	String	`pial`	(optional) pial attribute name
`--white`	String	`white`	(optional) white attribute name
`--parc`	String	`aparc`	(optional) parcellation attribute name
`--which`	String		(optional) only process certain parcellation labels (by default all will be processed)
`--mindist`	double	`1.0`	(optional) the minimum white-pial to be included
`--samples`	int	`15`	(optional) the number of points to sample
`--inner`	double	`2.0`	(optional) the inner buffer size
`--outer`	double	`2.0`	(optional) the outer buffer size
`--nofill`	flag		(optional) skip the filling step
`--smooth`	flag		(optional) apply fiber smoothing after projection
`--threads`	int	`1`	(optional) the number of threads

Advanced Parameters:

Flag	Type	Default	Description
`--name`	String	`name`	(optional) the name field in the lookup table
`--index`	String	`index`	(optional) the index field in the lookup table
`--sigma`	Double		(optional) apply smoothing with the given amount (bandwidth in mm) (default is largest voxel dimension)
`--support`	int	`3`	(optional) the smoothing filter radius in voxels

Output:

Flag	Type	Description
`--output`	Volume	the output vectors
`--labels`	Mask	(optional) the output labels

MeshGetVects

Extract a mesh vertex attribute as vectors

Input:

Flag	Type	Description
`--mesh`	Mesh	input mesh

Parameters:

Flag	Type	Default	Description
`--name`	String	`attr`	(optional) the destination attribute name

Output:

Flag	Type	Description
`--output`	Vects	output mesh

MeshGrow

Grow a mesh to fill a volume

Input:

Flag	Type	Description
`--input`	Mesh	the input mesh
`--reference`	Volume	the reference volume

Parameters:

Flag	Type	Default	Description
`--source`	String	`coord`	(optional) the source vertex attribute (default is the vertex position)
`--dest`	String	`shell`	(optional) the destination vertex attribute (the result will be saved here)
`--dist`	String	`dist`	(optional) the distance to the best match (the result will be saved here)
`--threshold`	double	`0.5`	(optional) the threshold
`--distance`	double	`20.0`	(optional) the maximums distance to search
`--step`	double	`0.25`	(optional) the maximums distance to search
`--invert`	flag		(optional) detect and increase past the threshold (the default is to detect the drop)
`--outside`	flag		(optional) search inside the mesh (the default is to search outside)
`--interp`	InterpolationType	`Trilinear`	(optional) image interpolation method (Options: Nearest, Trilinear, Tricubic, Gaussian, GaussianLocalLinear, GaussianLocalQuadratic)

Output:

Flag	Type	Description
`--output`	Mesh	the output mesh

MeshHoleFill

Fill holes in a mesh. This can be applied to either the entire mesh or a selection

Input:

Flag	Type	Description
`--input`	Mesh	the input mesh

Output:

Flag	Type	Description
`--output`	Mesh	the output mesh

MeshHull

Compute the convex hull of a mesh

Input:

Flag	Type	Description
`--input`	Mesh	input mesh

Output:

Flag	Type	Description
`--output`	Mesh	output hull mesh

Citation: Barber, C. B., Dobkin, D. P., & Huhdanpaa, H. (1996). The quickhull algorithm for convex hulls. ACM Transactions on Mathematical Software (TOMS), 22(4), 469-483.

MeshMapSphere

Convert a mesh between file formats

Input:

Flag	Type	Description
`--input`	Mesh	input mesh

Parameters:

Flag	Type	Default	Description
`--preiters`	int	`100`	(optional) the world space Laplacian smoothing iterations
`--iters`	int	`100`	(optional) the Laplacian smoothing iterations
`--lambmin`	double	`0.1`	(optional) the minimum Laplacian smoothing rate
`--lambmax`	double	`0.5`	(optional) the maximum Laplacian smoothing rate
`--gain`	double	`5.0`	(optional) the curvature gain

Output:

Flag	Type	Description
`--output`	Mesh	output mesh

MeshMath

Evaluate an expression at each vertex of a mesh

Input:

Flag	Type	Description
`--input`	Mesh	the input mesh

Parameters:

Flag	Type	Default	Description
`--expression`	String	`x > 0.5`	(optional) the expression to evaluate
`--result`	String	`result`	(optional) the attribute name for the result

Output:

Flag	Type	Description
`--output`	Mesh	output mesh

MeshMeasure

Measure global properties of a mesh

Input:

Flag	Type	Description
`--input`	Mesh	input mesh

Output:

Flag	Type	Description
`--output`	Table	output table

MeshMeasureRegion

Measure regional attributes properties of a mesh

Input:

Flag	Type	Description
`--input`	Mesh	input mesh
`--lookup`	Table	(optional) input lookup table
`--labels`	Vects	(optional) add the following per-vertex labeling to use for computing region statistics

Parameters:

Flag	Type	Default	Description
`--attr`	String		compute statistics of the following attributes (a comma-delimited list can be used)
`--output`	String		output directory
`--label`	String	`label`	(optional) use the given vertex attribute to identify regions and compute statistics
`--lutname`	String	`name`	(optional) the lookup name field
`--lutindex`	String	`index`	(optional) the lookup index field
`--outname`	String	`name`	(optional) the output name field
`--outvalue`	String	`value`	(optional) the output value field

MeshNormals

Compute vertex normals of a mesh

Input:

Flag	Type	Description
`--input`	Mesh	the input mesh

Parameters:

Flag	Type	Default	Description
`--attr`	String	`coord`	(optional) the mesh attribute
`--smooth`	int	`0`	(optional) the number of smoothing iterations

Output:

Flag	Type	Description
`--output`	Mesh	the output mesh

MeshPrintInfo

Print basic information about a mesh

Input:

Flag	Type	Description
`--input`	Mesh	the input mesh

Parameters:

Flag	Type	Default	Description
`--stats`	flag		(optional) print statistics
`--area`	flag		(optional) print statistics of triangle areas

MeshResampleSphere

Resample a spherically parameterized mesh using a new spherical triangulation

Input:

Flag	Type	Description
`--input`	Mesh	input mesh to be resampled
`--reference`	Mesh	reference spherical mesh with the new triangulation

Parameters:

Flag	Type	Default	Description
`--inputSphereAttr`	String	`sphere`	(optional) the input mesh spherical coordinate attribute
`--refSphereAttr`	String	`coord`	(optional) the reference mesh spherical coordinate attribute
`--labels`	String	``	(optional) a comma-separated list of input attributes that are discrete labels (if any)
`--skips`	String	``	(optional) a comma-separated list of the input attributes that should be skipped (if any)

Output:

Flag	Type	Description
`--output`	Mesh	output mesh

MeshSample

Sample a volume at input vertices

Input:

Flag	Type	Description
`--input`	Mesh	input input
`--volume`	Volume	input volume

Parameters:

Flag	Type	Default	Description
`--interp`	InterpolationType	`Trilinear`	(optional) interpolation method (Options: Nearest, Trilinear, Tricubic, Gaussian, GaussianLocalLinear, GaussianLocalQuadratic)
`--coord`	String	`coord`	(optional) coord attribute name (used for sampling volume)
`--attr`	String	`sampled`	(optional) output attribute name (where the sampled image data will be stored)
`--window`	Double		(optional) compute a statistical summary of image intensities sampled along points within a certain window of each vertex (units: mm), sampled along the surface normal direction
`--sample`	MeshSampleDirection	`Both`	(optional) compute the statistical summary in a given direction (default is both inside and outside the mesh) (Options: Both, Inside, Outside)
`--stat`	MeshSampleStatistic	`Mean`	(optional) use the given statistic for summarizing the vertex window (Options: Mean, Min, Max)

Output:

Flag	Type	Description
`--output`	Mesh	the output mesh

MeshSelect

Select vertices of a mesh

Input:

Flag	Type	Description
`--input`	Mesh	the input mesh
`--solids`	Solids	(optional) some solids

Parameters:

Flag	Type	Default	Description
`--boundary`	flag		(optional) select the boundary
`--invert`	flag		(optional) invert the selection
`--attr`	String	`selection`	(optional) the selection attribute
`--value`	double	`1.0`	(optional) the selection value

Output:

Flag	Type	Description
`--output`	Mesh	the output mesh

MeshSetTable

Create a table listing regions of a mask

Input:

Flag	Type	Description
`--mesh`	Mesh	input mesh
`--table`	Table	input table
`--lookup`	Table	(optional) a lookup table to relate names to indices

Parameters:

Flag	Type	Default	Description
`--merge`	String	`name`	(optional) a field name to merge on
`--index`	String	`index`	(optional) the table index field name
`--value`	String	`value`	(optional) a table field to get (can be comma delimited)
`--mindex`	String		(optional) the mesh index field name (defaults to table index field name)
`--mvalue`	String		(optional) the mesh value field name (defaults to table value field name)
`--background`	double	`0.0`	(optional) a background value
`--missing`	Double		(optional) an missing value
`--remove`	flag		(optional) remove triangles with vertices that are not included in the input table

Output:

Flag	Type	Description
`--output`	Mesh	output mesh

MeshSetVects

Add vects as an attribute on a mesh (number of vects must match the number of vertices)

Input:

Flag	Type	Description
`--mesh`	Mesh	input mesh
`--vects`	Vects	input vects

Parameters:

Flag	Type	Default	Description
`--name`	String	`attr`	(optional) the destination attribute name

Output:

Flag	Type	Description
`--output`	Mesh	output mesh

MeshSimplify

Simplify a input by removing short edges

Input:

Flag	Type	Description
`--input`	Mesh	the input mesh

Parameters:

Flag	Type	Default	Description
`--maxiter`	Integer	`10000`	(optional) maxima number of iterations
`--maxvert`	Integer		(optional) maxima number of vertices
`--maxedge`	Integer		(optional) maxima number of edges
`--maxface`	Integer		(optional) maxima number of faces
`--meanarea`	Double		(optional) maxima average face surface area
`--nobound`	flag		(optional) do not remove boundary vertices
`--chatty`	flag		(optional) print messages

Output:

Flag	Type	Description
`--output`	Mesh	the output mesh

MeshSmooth

Smooth a mesh

Input:

Flag	Type	Description
`--input`	Mesh	the input

Parameters:

Flag	Type	Default	Description
`--attr`	String	`coord`	(optional) the attribute to smooth
`--attrout`	String		(optional) the output attribute names (if none, the input is replaced)
`--num`	int	`5`	(optional) a number of iterations
`--lambda`	Double	`0.3`	(optional) the lambda laplacian smoothing parameter
`--mu`	Double		(optional) the optional mu parameter for Taubin’s method

Output:

Flag	Type	Description
`--output`	Mesh	the output mesh

Citation: Taubin, G. (1995, September). A signal processing approach to fair surface design. In Proceedings of the 22nd annual conference on Computer graphics and interactive techniques (pp. 351-358). ACM.

MeshSubdivide

Subdivide a mesh. Each triangle is split into four with new vertices that split each edge in two.

Input:

Flag	Type	Description
`--input`	Mesh	the input mesh

Parameters:

Flag	Type	Default	Description
`--num`	int	`1`	(optional) a number of subdivisions

Output:

Flag	Type	Description
`--output`	Mesh	the output mesh

MeshTable

Create a table from mesh vertex attributes

Input:

Flag	Type	Description
`--input`	Mesh	input input

Parameters:

Flag	Type	Default	Description
`--vertices`	String		(optional) which vertices retain (comma separated)
`--which`	String	`coord`	(optional) which attributes to retain (comma separated)

Output:

Flag	Type	Description
`--output`	Table	output table

MeshTransform

Transform a mesh

Input:

Flag	Type	Description
`--input`	Mesh	input mesh
`--affine`	Affine	(optional) apply an affine xfm
`--invaffine`	Affine	(optional) apply an inverse affine xfm
`--deform`	Deformation	(optional) apply a deformation xfm
`--pose`	Volume	(optional) apply a transform to match the pose of a volume
`--invpose`	Volume	(optional) apply a transform to match the inverse pose of a volume

Parameters:

Flag	Type	Default	Description
`--reverse`	flag		(optional) reverse the order, i.e. compose the affine(deform(x)), whereas the default is deform(affine(x))
`--attrs`	String	`coord`	(optional) a comma-separated list of attributes to transform
`--tx`	Double		(optional) translate the mesh in by the given about in the x dimension
`--ty`	Double		(optional) translate the mesh in by the given about in the y dimension
`--tz`	Double		(optional) translate the mesh in by the given about in the z dimension
`--sx`	Double		(optional) scale the mesh in by the given about in the x dimension
`--sy`	Double		(optional) scale the mesh in by the given about in the y dimension
`--sz`	Double		(optional) scale the mesh in by the given about in the z dimension

Output:

Flag	Type	Description
`--output`	Mesh	output mesh

MeshVertices

Extract the vertices of a mesh

Input:

Flag	Type	Description
`--input`	Mesh	input mesh

Parameters:

Flag	Type	Default	Description
`--attribute`	String	`coord`	(optional) attribute to extract
`--query`	String	`label`	(optional) an attribute to query
`--value`	Integer		(optional) an integer value to query
`--nonzero`	flag		(optional) select only vertices that have a non-zero query attribute

Output:

Flag	Type	Description
`--output`	Vects	output vects

MeshVoxelize

Voxelize a mesh to a mask (should be watertight if the mesh is also)

Input:

Flag	Type	Description
`--input`	Mesh	input input
`--reference`	Mask	reference mask

Parameters:

Flag	Type	Default	Description
`--label`	Integer	`1`	(optional) a label to draw
`--attr`	String		(optional) a attribute to draw (instead of the constant label)
`--coord`	String	`coord`	(optional) the coordinate attribute to use (not applicable when specifying inner and outer shells)
`--innerAttr`	String		(optional) label vertices in a shell between an inner and outer spatial attribute, e.g. like white and pial cortical surfaces
`--outerAttr`	String		(optional) label vertices in a shell between an inner and outer spatial attribute, e.g. like white and pial cortical surfaces
`--innerBuffer`	Double		(optional) label vertices in a shell between this attribute and the primary one, e.g. like white and pial cortical surfaces
`--outerBuffer`	Double		(optional) label vertices in a shell between this attribute and the primary one, e.g. like white and pial cortical surfaces
`--fill`	flag		(optional) fill the inside of the mask

Output:

Flag	Type	Description
`--output`	Mask	the output mask

NeuronCatPair

Combine two neurons into a single object

Input:

Flag	Type	Description
`--left`	Neuron	the input left neuron
`--right`	Neuron	the input right neuron

Output:

Flag	Type	Description
`--output`	Neuron	output neuron

NeuronCrossing

Detect the crossing points between two neurons

Input:

Flag	Type	Description
`--left`	Neuron	the input left neuron
`--right`	Neuron	the input right neuron

Parameters:

Flag	Type	Default	Description
`--thresh`	Double		(optional) the minimum distance to be considered a crossing (by default it will be the average inter-node distance)
`--mode`	NeuronCrossingMode	`Mean`	(optional) specify a statistic for computing the threshold (not relevant if you provide a specific value) (Options: Min, Max, Mean)

Output:

Flag	Type	Description
`--output`	Vects	output vects

NeuronExport

Export a neuron file to vects and curves

Input:

Flag	Type	Description
`--input`	Neuron	the input filename to the SWC neuron file

Output:

Flag	Type	Description
`--outputRoots`	Vects	(optional) output roots
`--outputForks`	Vects	(optional) output forks
`--outputLeaves`	Vects	(optional) output leaves
`--outputForest`	Curves	(optional) output forest

NeuronFilter

Filter a neuron

Input:

Flag	Type	Description
`--input`	Neuron	the input neuron

Parameters:

Flag	Type	Default	Description
`--which`	String		(optional) select only the neurons with the given root labels (comma-separated list)
`--laplacianIters`	Integer		(optional) apply laplacian smoothing the given number of times
`--laplacianLambda`	Double	`0.25`	(optional) the smoothing weight for laplacian smoothing (only relevant if smoothing is enabled)
`--lowessNum`	Integer		(optional) apply lowess smoothing with the given neighborhood size, e.g. 5
`--lowessOrder`	Integer	`2`	(optional) apply lowess smoothing with the given local polynomial order
`--simplify`	Double		(optional) simplify the neuron segments with the Douglas-Peucker algorithm
`--cut`	Double		(optional) cut away the portion of the neuron past the given Euclidean distance away from the root

Advanced Parameters:

Flag	Type	Description
`--relabel`	flag	(optional) relabel the nodes to be sequential
`--sort`	flag	(optional) perform a topological sorting of nodes
`--debase`	flag	(optional) separate the basal dendrite (detected by the soma branch with the farthest reach)

Output:

Flag	Type	Description
`--output`	Neuron	output neuron

NeuronMeasure

Measure statistics of a neuron file

Input:

Flag	Type	Description
`--input`	Neuron	the input neuron

Parameters:

Flag	Type	Default	Description
`--single`	flag		(optional) include statistics for single neurons

Output:

Flag	Type	Description
`--output`	Table	output table

NeuronMesh

Create a mesh from a neuron file

Input:

Flag	Type	Description
`--input`	Neuron	the input filename to the SWC neuron file

Parameters:

Flag	Type	Default	Description
`--noRootMesh`	flag		(optional) exclude sphere meshes for roots
`--noForkMesh`	flag		(optional) exclude sphere meshes for forks
`--noLeafMesh`	flag		(optional) exclude sphere meshes for leaves
`--noTrunkMesh`	flag		(optional) exclude tube meshes for trunks
`--noSphereSculpt`	flag		(optional) use constant radius for spheres (the default will modulate the thickness by the neuron radius)
`--noTrunkSculpt`	flag		(optional) use constant thickness tubes (the default will modulate the thickness by the neuron radius)
`--trunkColorMode`	TrunkColorMode	`Solid`	(optional) the coloring mode for trunks (Options: Solid, DEC, Segment, Tree)
`--rootScale`	double	`1.0`	(optional) the size of root spheres
`--forkScale`	double	`1.0`	(optional) the size of fork spheres
`--leafScale`	double	`1.0`	(optional) the size of leaf spheres
`--trunkScale`	double	`1.0`	(optional) the size of trunk tubes
`--rootColor`	SolidColor	`Orange`	(optional) the color of root spheres (Options: White, Cyan, Yellow, Blue, Magenta, Orange, Green, Pink, GRAY, DarkGray, LightGray)
`--forkColor`	SolidColor	`Cyan`	(optional) the color of fork spheres (Options: White, Cyan, Yellow, Blue, Magenta, Orange, Green, Pink, GRAY, DarkGray, LightGray)
`--leafColor`	SolidColor	`Yellow`	(optional) the color of leaf spheres (Options: White, Cyan, Yellow, Blue, Magenta, Orange, Green, Pink, GRAY, DarkGray, LightGray)
`--trunkColor`	SolidColor	`White`	(optional) the color of trunk tubes (if the coloring mode is solid) (Options: White, Cyan, Yellow, Blue, Magenta, Orange, Green, Pink, GRAY, DarkGray, LightGray)
`--noColor`	flag		(optional) remove all colors (and invalidates any other color options)
`--sphereResolution`	int	`0`	(optional) the resolution of the spheres i.e. the number of subdivisions, so be careful with values above 3
`--tubeResolution`	int	`5`	(optional) the resolution of the tubes, i.e. the number of radial spokes

Output:

Flag	Type	Description
`--output`	Mesh	output mesh

NeuronPrintInfo

Measure statistics of a neuron file

Input:

Flag	Type	Description
`--input`	Neuron	the input neuron

NeuronSplit

Split a SWC file to produce a single file per neuron

Input:

Flag	Type	Description
`--input`	Neuron	the input neuron

Parameters:

Flag	Type	Default	Description
`--output`	String		output filename (if you include %d, it will be substituted with the root label, otherwise it will be renamed automatically)
`--root`	flag		(optional) use the root neuron label for naming the output file (i.e. the number substituted for %d)

NeuronStitch

Perform stitching to build neuron segments into a complete neuron. The neuron will be split into pieces and rebuilt.

Input:

Flag	Type	Description
`--input`	Neuron	the input neuron
`--somas`	Solids	(optional) a solids object for manually defining somas for stitching, e.g. each box and sphere will define a region for building somas (only used when the soma mode is Manual)

Parameters:

Flag	Type	Default	Description
`--mode`	NeuronStitchSomaMode	`RadiusMax`	(optional) choose a mode for selecting the soma(s). Manual selection is for user-defined soma (from a solids object passed to the somas option). RadiusMax is for choosing the soma from the node with the largest radius. Cluster is for detecting the soma by clustering endpoints and finding the largest cluster (depends on the cluster option for defining the cluster spatial extent) (Options: Manual, RadiusMax, Cluster)
`--threshold`	Double		(optional) a maximum distance for stitching together segments. If two segments are farther than this distance, they will not be stitched (default is to stitch everything
`--cluster`	Double		(optional) a specific radius for cluster-based soma selection (only used for the Cluster soma detection mode)

Output:

Flag	Type	Description
`--output`	Neuron	output neuron

NeuronTransform

Apply a spatial transformation to a neuron

Input:

Flag	Type	Description
`--input`	Neuron	the neuron
`--affine`	Affine	(optional) apply an affine xfm
`--invaffine`	Affine	(optional) apply an inverse affine xfm

Parameters:

Flag	Type	Default	Description
`--xshift`	double	`0.0`	(optional) translate the neuron position in x by the given amount
`--yshift`	double	`0.0`	(optional) translate the neuron position in y by the given amount
`--zshift`	double	`0.0`	(optional) translate the neuron position in z by the given amount
`--xscale`	double	`1.0`	(optional) scale the neuron position in x by the given amount
`--yscale`	double	`1.0`	(optional) scale the neuron position in y by the given amount
`--zscale`	double	`1.0`	(optional) scale the neuron position in z by the given amount
`--rshift`	double	`0.0`	(optional) add the given amount to the radius
`--rscale`	double	`1.0`	(optional) scale the neuron radius by the given amount
`--rset`	Double		(optional) set the radius to a constant value
`--jitter`	Double		(optional) jitter the position of the nodes by a random amount
`--jitterEnds`	flag		(optional) jitter only leaves and roots
`--swap`	String		(optional) swap a pair of coordinates (xy, xz, or yz)

Output:

Flag	Type	Description
`--output`	Neuron	output neuron

SolidsBox

Compute the bounding box of solids

Input:

Flag	Type	Description
`--input`	Solids	input solids

Output:

Flag	Type	Description
`--output`	Solids	output bounding box

SolidsCat

Concatenate solids

Input:

Flag	Type	Description
`--left`	Solids	input solids
`--right`	Solids	input solids

Output:

Flag	Type	Description
`--output`	Solids	output solids

SolidsConvert

Convert solids between file formats

Input:

Flag	Type	Description
`--input`	Solids	input solids

Output:

Flag	Type	Description
`--output`	Solids	output sphere

SolidsCreateBox

Create a soilds object containing a box

Parameters:

Flag	Type	Default	Description
`--xmin`	double	`0.0`	(optional) a box minima value in x
`--ymin`	double	`0.0`	(optional) a box minima in y
`--zmin`	double	`0.0`	(optional) a box minima in z
`--xmax`	double	`1.0`	(optional) a box maxima value in x
`--ymax`	double	`1.0`	(optional) a box maxima in y
`--zmax`	double	`1.0`	(optional) a box maxima in z

Output:

Flag	Type	Description
`--output`	Solids	output solids

SolidsCreateEmpty

Create an empty soilds object

Output:

Flag	Type	Description
`--output`	Solids	output solids

SolidsCreatePlane

Create a soilds object containing a plane

Parameters:

Flag	Type	Default	Description
`--xpoint`	double	`0.0`	(optional) the x coordinate of a point on the plane
`--ypoint`	double	`0.0`	(optional) the y coordinate of a point on the plane
`--zpoint`	double	`0.0`	(optional) the z coordinate of a point on the plane
`--xnormal`	double	`0.0`	(optional) the x coordinate of the plane normal
`--ynormal`	double	`0.0`	(optional) the y coordinate of the plane normal
`--znormal`	double	`0.0`	(optional) the z coordinate of the plane normal

Output:

Flag	Type	Description
`--output`	Solids	output solids

SolidsCreateSphere

Create a soilds object containing a sphere

Parameters:

Flag	Type	Default	Description
`--x`	double	`0.0`	(optional) a sphere x center
`--y`	double	`0.0`	(optional) a sphere y center
`--z`	double	`0.0`	(optional) a sphere z center
`--radius`	double	`10.0`	(optional) a sphere radius

Output:

Flag	Type	Description
`--output`	Solids	output solids

SolidsMask

Create a mask from solids

Input:

Flag	Type	Description
`--input`	Solids	input solids

Parameters:

Flag	Type	Default	Description
`--dx`	double	`1.0`	(optional) sample spacing in x
`--dy`	double	`1.0`	(optional) sample spacing in x
`--dz`	double	`1.0`	(optional) sample spacing in x
`--label`	int	`1`	(optional) label

Output:

Flag	Type	Description
`--output`	Mask	output mask

SolidsMesh

Create a mask from solids

Input:

Flag	Type	Description
`--input`	Solids	input solids

Parameters:

Flag	Type	Default	Description
`--delta`	double	`1.0`	(optional) the voxel resolution for discretization

Output:

Flag	Type	Description
`--output`	Mesh	output mesh

SolidsPrintInfo

Print basic information about a solids

Input:

Flag	Type	Description
`--input`	Solids	the input solids

SolidsSample

Sample vects inside solids

Input:

Flag	Type	Description
`--input`	Solids	input solids

Parameters:

Flag	Type	Default	Description
`--num`	int	`100`	(optional) the number of points to sample

Output:

Flag	Type	Description
`--output`	Vects	output sampled vects

SolidsToWaypoints

Create a waypoint mask from two solids

Input:

Flag	Type	Description
`--a`	Solids	first input set of solids
`--b`	Solids	second input set of solids
`--ref`	Mask	input reference mask

Output:

Flag	Type	Description
`--output`	Mask	output waypoint mask

TableCat

Concatenate the rows of two tables. By default, it will only include fields that are common to both input tables.

Input:

Flag	Type	Description
`--x`	Table	(optional) input first table
`--y`	Table	(optional) input second table

Parameters:

Flag	Type	Default	Description
`--outer`	flag		(optional) include all possible fields

Output:

Flag	Type	Description
`--output`	Table	output table

TableConvert

Convert a table between file formats

Input:

Flag	Type	Description
`--input`	Table	input table

Output:

Flag	Type	Description
`--output`	Table	output table

TableDistanceMatrix

Create a distance matrix from pairs of distances

Input:

Flag	Type	Description
`--input`	Table	input table (should have field for the left and right identifiers)

Parameters:

Flag	Type	Default	Description
`--left`	String	`left`	(optional) the identifier for left values
`--right`	String	`right`	(optional) the identifier for right values
`--value`	String	`value`	(optional) the identifier for right values

Output:

Flag	Type	Description
`--output`	Table	output table

TableFilter

Filter a table, a few options are available

Input:

Flag	Type	Description
`--input`	Table	input table
`--volumes`	Table	add a field for the mean value based on a table of volumes for each field (this is an unusual need)

Parameters:

Flag	Type	Default	Description
`--meanField`	String	`mean`	(optional) the name of the field for saving the mean value
`--mergeField`	String	`subject`	(optional) the name of the field for merging tables
`--missing`	String	`NA`	(optional) a token for missing values

Output:

Flag	Type	Description
`--output`	Table	output table

TableHemiMean

Compute the left-right average of a lateralized dataset

Input:

Flag	Type	Description
`--input`	Table	input table (should use the naming convention like the module parameters)

Parameters:

Flag	Type	Default	Description
`--left`	String	`lh_`	(optional) the identifier for left values
`--right`	String	`rh_`	(optional) the identifier for right values

Output:

Flag	Type	Description
`--output`	Table	output table

TableLaterality

Compute the lateralization index of a given map. This assumes you have a two column table (name,value) that contains left and right measurements (see module parameters to specify the left/right identifiers)

Input:

Flag	Type	Description
`--input`	Table	input table (should use the naming convention like the module parameters)

Parameters:

Flag	Type	Default	Description
`--left`	String	`lh_`	(optional) the identifier for left values
`--right`	String	`rh_`	(optional) the identifier for right values
`--indlat`	String	`indlat_`	(optional) the identifier for the lateralization index
`--abslat`	String	`abslat_`	(optional) the identifier for the absolute lateralization index
`--unilat`	String	`unilat_`	(optional) the identifier for the unilateral averaging
`--minlat`	String	`minlat_`	(optional) the identifier for the left right minimum
`--maxlat`	String	`maxlat_`	(optional) the identifier for the left right maximum

Output:

Flag	Type	Description
`--output`	Table	output table

TableLateralityIndex

Compute the lateralization index of a given map. This assumes you have a two column table (name,value) that contains left and right measurements (see module parameters to specify the left/right identifiers)

Input:

Flag	Type	Description
`--input`	Table	input table (should use the naming convention like the module parameters)

Parameters:

Flag	Type	Default	Description
`--name`	String	`name`	(optional) the field holding the name of the measurement
`--value`	String	`value`	(optional) the field holding the value of the measurement
`--left`	String	`lh_`	(optional) the identifier for left values
`--right`	String	`rh_`	(optional) the identifier for right values
`--lat`	String	`lat_`	(optional) the identifier for the lateralization index
`--abslat`	String	`abslat_`	(optional) the identifier for the absolute lateralization index
`--mean`	String	`mean_`	(optional) the identifier for the left-right average

Output:

Flag	Type	Description
`--output`	Table	output table

TableMapMath

Evaluate an expression with a map (a table listing name/value pairs)

Input:

Flag	Type	Description
`--input`	Table	the input table map

Parameters:

Flag	Type	Default	Description
`--expression`	String	`x > 0.5`	(optional) the expression to evaluate
`--name`	String	`name`	(optional) the field name for the name
`--value`	String	`value`	(optional) the field name for the value
`--result`	String	`result`	(optional) the name of the result

Output:

Flag	Type	Description
`--output`	Table	output table

TableMath

Evaluate an expression for each row of a table

Input:

Flag	Type	Description
`--input`	Table	the input table

Parameters:

Flag	Type	Default	Description
`--expression`	String	`x > 0.5`	(optional) the expression to evaluate
`--result`	String	`result`	(optional) the field name for the result
`--na`	String	`NA`	(optional) the string used for invalid values

Output:

Flag	Type	Description
`--output`	Table	output table

TableMerge

Merge two tables based the value of a shared field

Input:

Flag	Type	Description
`--left`	Table	input left table
`--right`	Table	input right table

Parameters:

Flag	Type	Default	Description
`--field`	String	`name`	(optional) the common field to merge on
`--leftPrefix`	String	``	(optional) add a prefix to the fields from the left table
`--rightPrefix`	String	``	(optional) add a prefix to the fields from the right table
`--leftPostfix`	String	``	(optional) add a postfix to the fields from the left table
`--rightPostfix`	String	``	(optional) add a postfix to the fields from the right table

Advanced Parameters:

Flag	Type	Default	Description
`--leftField`	String		(optional) use the given left field (instead of the shared merge field)
`--rightField`	String		(optional) use the given right field (instead of the shared merge field)

Output:

Flag	Type	Description
`--output`	Table	output table

TableNarrow

Narrow a table to reduce the number of fields

Input:

Flag	Type	Description
`--input`	Table	input table

Parameters:

Flag	Type	Default	Description
`--name`	String	`name`	(optional) the new field for each field name
`--value`	String	`value`	(optional) the new field for each field value
`--keep`	String		(optional) fields to keep (comma separated)

Output:

Flag	Type	Description
`--output`	Table	output table

TableOutliers

Compute z-scores to detect outliers in a table

Input:

Flag	Type	Description
`--input`	Table	input table

Output:

Flag	Type	Description
`--output`	Table	output table

TablePrintData

Print data from a table

Input:

Flag	Type	Description
`--input`	Table	the input table

Parameters:

Flag	Type	Default	Description
`--where`	String		(optional) an predicate for selecting records (using existing field names)
`--name`	String	`name`	(optional) the name variable for use in the select predicate
`--sort`	String		(optional) sort by fields (e.g. field2,#field3,^#field1). ‘#’ indicates the value is numeric, and ‘^’ indicates the sorting should be reversed
`--retain`	String		(optional) retain only specific fields (comma delimited)
`--remove`	String		(optional) remove specific fields (comma delimited)
`--tab`	flag		(optional) use tabs
`--header`	flag		(optional) print the header
`--na`	String	`NA`	(optional) use the given string for missing values

TablePrintInfo

Print basic information about a table

Input:

Flag	Type	Description
`--input`	Table	the input table

Parameters:

Flag	Type	Default	Description
`--na`	String	`NA`	(optional) specify the token for identifying missing values
`--field`	String		(optional) only print values from the given field (specify either the field index or name)
`--pattern`	String		(optional) print a pattern for each line, e.g. ‘${fieldA} and ${fieldB}
`--indexed`	flag		(optional) print the row index

TableReliability

Compute reproducibility statistics from repeated measures

Input:

Flag	Type	Description
`--input`	Table	input table

Parameters:

Flag	Type	Default	Description
`--value`	String	`value`	(optional) the field to summarize
`--id`	String		(optional) fields for identifying repeated measures (comma separated)
`--group`	String		(optional) fields to group records by (comma separated)

Output:

Flag	Type	Description
`--output`	Table	output table

TableScoreZ

Compute summary statistics of a field of a table

Input:

Flag	Type	Description
`--input`	Table	input table

Parameters:

Flag	Type	Default	Description
`--value`	String	`value`	(optional) the field to summarize
`--absolute`	flag		(optional) report the absolute value of the z-score
`--group`	String		(optional) fields to group records by (comma separated)

Output:

Flag	Type	Description
`--output`	Table	output table

TableSelect

Select columns from a table

Input:

Flag	Type	Description
`--input`	Table	input table

Parameters:

Flag	Type	Description
`--where`	String	(optional) an predicate for selecting records (using existing field names)
`--sort`	String	(optional) sort by fields (e.g. field2,#field3,^#field1). ‘#’ indicates the value is numeric, and ‘^’ indicates the sorting should be reversed
`--unique`	String	(optional) select a unique set from the given fields (comma delimited)
`--retain`	String	(optional) include only specific fields (comma delimited regular expressions)
`--remove`	String	(optional) exclude specific fields (comma delimited regular expressions)
`--rename`	String	(optional) an renaming of fields (e.g. newfield=oldfield)
`--dempty`	flag	(optional) delete fields with an empty name
`--cat`	String	(optional) concatenate existing fields into a new one, e.g. newfield=%{fieldA}_%{fieldB}
`--constant`	String	(optional) add a constant field (e.g. newfield=value,newfield2=value2)

Output:

Flag	Type	Description
`--output`	Table	output table

TableSplitAlong

Split the name field from along tract analysis

Input:

Flag	Type	Description
`--input`	Table	input table

Parameters:

Flag	Type	Default	Description
`--name`	String	`name`	(optional) the field to split
`--bundle`	String	`bundle`	(optional) the name of the new bundle field
`--index`	String	`index`	(optional) the name of the new index field
`--delimiter`	String	`_`	(optional) the delimiter

Output:

Flag	Type	Description
`--output`	Table	output table

TableStats

Compute summary statistics of a field of a table

Input:

Flag	Type	Description
`--input`	Table	input table

Parameters:

Flag	Type	Default	Description
`--value`	String	`value`	(optional) the field to summarize
`--group`	String		(optional) fields to group records by (comma separated)
`--pattern`	String	`%s`	(optional) a pattern for saving statistics (contains %s)
`--which`	String	`mean,std`	(optional) which statistics to include (mean, min, max, sum, var, std, num, cv)

Output:

Flag	Type	Description
`--output`	Table	output table

TableSubjectMatch

Match subjects into pairs. You should provide a field that stores a binary variable on which to split. The smaller group will be paired with subjects from the bigger group, and optionally, the pairing can be optimized to maximize similarity between paired individuals based on a number of scalar and discrete variables

Input:

Flag	Type	Description
`--input`	Table	input table

Parameters:

Flag	Type	Default	Description
`--subject`	String	`subject`	(optional) the field specifying the subject identifier
`--split`	String	`subject`	(optional) the field for splitting the group (should be binary)
`--na`	String	`NA`	(optional) a token for specifying missing data
`--distance`	String	`distance`	(optional) the field name for distance in the output
`--scalar`	String	``	(optional) scalar fields to include when computing subject distances (comma separated list)
`--discrete`	String	``	(optional) discrete fields to include when computing subject distances (comma separated list)

Output:

Flag	Type	Description
`--output`	Table	output table

TableSynth

Synthesize data based on a reference dataset

Input:

Flag	Type	Description
`--reference`	Table	input reference table
`--sample`	Table	input sample table

Parameters:

Flag	Type	Default	Description
`--group`	String		(optional) an optional list of variables (comma-separated) of variables for grouping
`--scalar`	String		(optional) specify the scalar-valued fields (floating point)
`--discrete`	String		(optional) specify the discrete-valued fields (integers)
`--factor`	String		(optional) specify the categorical-valued fields (factors)
`--missing`	flag		(optional) synthesize missing data
`--na`	String	`NA`	(optional) specify a missing value token

Output:

Flag	Type	Description
`--output`	Table	output synthesized table

TableVolume

Map tabular data to a volume

Input:

Flag	Type	Description
`--input`	Table	input table
`--reference`	Mask	a reference mask

Parameters:

Flag	Type	Default	Description
`--vector`	flag		(optional) read vector values
`--voxel`	String	`index`	(optional) index
`--value`	String	`value`	(optional) value
`--na`	double	`0.0`	(optional) a value to substitute for NAs

Output:

Flag	Type	Description
`--output`	Volume	output volume

TableWiden

Widen a table to expand a single field to many

Input:

Flag	Type	Description
`--input`	Table	input table

Parameters:

Flag	Type	Default	Description
`--name`	String	`name`	(optional) the field name to expand
`--value`	String	`value`	(optional) the field value to expand
`--pattern`	String	`%s_%s`	(optional) pattern for joining names
`--na`	String	`NA`	(optional) the value used for missing entries
`--include`	String		(optional) include fields
`--exclude`	String		(optional) exclude fields

Output:

Flag	Type	Description
`--output`	Table	output table

VectsAlignAxis

Compute an affine transform to align a set of points to the z-axis

Input:

Flag	Type	Description
`--input`	Vects	input vects (should be roughly linear

Output:

Flag	Type	Description
`--output`	Affine	output affine transform

VectsBox

Get the bounding box of vects

Input:

Flag	Type	Description
`--input`	Vects	input vects

Output:

Flag	Type	Description
`--output`	Solids	output bounding box

VectsCat

Concatenate two sets of vectors into one

Input:

Flag	Type	Description
`--input`	Vects	input vects
`--cat`	Vects	vects to concatenate

Parameters:

Flag	Type	Default	Description
`--dims`	flag		(optional) concatenate dimensions (instead of vects)

Output:

Flag	Type	Description
`--output`	Vects	output concatenated vects

VectsClusterKMeans

Cluster vects using k-means or DP-means clustering

Input:

Flag	Type	Description
`--input`	Vects	the input vects

Parameters:

Flag	Type	Default	Description
`--k`	Integer	`3`	(optional) none
`--lambda`	Double		(optional) none
`--maxiter`	Integer	`300`	(optional) none

Output:

Flag	Type	Description
`--centers`	Vects	(optional) the output cluster centeres
`--output`	Vects	(optional) the output clustered vects (last coordinate stores label)

VectsConvert

Convert vects between file formats

Input:

Flag	Type	Description
`--input`	Vects	input vects

Output:

Flag	Type	Description
`--output`	Vects	output vects

VectsCreate

Create vects

Output:

Flag	Type	Description
`--output`	Vects	output vects

VectsCreateSphere

Create vects that lie on a sphere by subdividing an icosahedron

Parameters:

Flag	Type	Default	Description
`--subdiv`	int	`3`	(optional) the number of subdivisions of the sphere
`--smooth`	Integer		(optional) the number of smoothing iterations
`--points`	Integer		(optional) reduce the point count

Output:

Flag	Type	Description
`--output`	Vects	output vects

VectsCreateSphereLookup

Create a set of uniformly distributed spherical points from a lookup table

Output:

Flag	Type	Description
`--output`	Vects	output vects

VectsDistances

Compute the pairwise distance matrix of a set of vects

Input:

Flag	Type	Description
`--input`	Vects	input vects

Output:

Flag	Type	Description
`--output`	Matrix	output distance matrix

VectsFuseKernel

Fuse a collection of vectors using kernel regression

Input:

Flag	Type	Description
`--table`	Table	(optional) input table

Parameters:

Flag	Type	Default	Description
`--input`	String		an input pattern (must contain %s for case identifier)
`--output`	String		output file pattern (must include a %s)
`--id`	String	`id`	(optional) the name of the case identifier (the table should have a column by this name)
`--scalar`	String		(optional) the continuous variable, if none is provided then no sampling is performed
`--samples`	String	`1,2,3,4,5,6,7,8,9,10`	(optional) the values for scalar variable sampling
`--sigma`	double	`5.0`	(optional) the bandwidth for scalar variable sampling

VectsHistogram

Compute a histogram of a vects

Input:

Flag	Type	Description
`--input`	Vects	the input vects

Parameters:

Flag	Type	Default	Description
`--channel`	int	`0`	(optional) the channel to use
`--bins`	int	`100`	(optional) the number of bins
`--lower`	Bound	`Extrema`	(optional) the method for computing the histogram lower bound (Options: Extrema, Quartile, HalfStd, OneStd, TwoStd, ThreeStd, User)
`--upper`	Bound	`Extrema`	(optional) the method for computing the histogram upper bound (Options: Extrema, Quartile, HalfStd, OneStd, TwoStd, ThreeStd, User)
`--mylower`	Double		(optional) specify a specific lower bound for user defined mode
`--myupper`	Double		(optional) specify a specific upper bound for user defined mode
`--normalize`	flag		(optional) normalize the counts by the total count
`--cdf`	flag		(optional) compute the cdf
`--smooth`	Double		(optional) apply Gaussian smoothing (see hdata)
`--hdata`	flag		(optional) interpret the smoothing parameter relative to the data intensities (default is bins)
`--print`	flag		(optional) print a the histogram to standard output

VectsHull

Compute the convex hull of vects

Input:

Flag	Type	Description
`--input`	Vects	input vects

Output:

Flag	Type	Description
`--output`	Mesh	output convex hull

Citation: Barber, C. B., Dobkin, D. P., & Huhdanpaa, H. (1996). The quickhull algorithm for convex hulls. ACM Transactions on Mathematical Software (TOMS), 22(4), 469-483.

VectsJitter

Jitter vects with isotropic Gaussian random displacements

Input:

Flag	Type	Description
`--input`	Vects	input vects

Parameters:

Flag	Type	Default	Description
`--multiplier`	int	`1`	(optional) the number of multiples to include
`--std`	double	`1.0`	(optional) the number of samples to take

Output:

Flag	Type	Description
`--output`	Vects	output subsampled vects

VectsMath

Evaluate an expression at each vector

Input:

Flag	Type	Description
`--input`	Vects	the input vects

Parameters:

Flag	Type	Default	Description
`--expression`	String	`mean(v)`	(optional) the expression to evaluate

Output:

Flag	Type	Description
`--output`	Vects	output vects

VectsMeasureRegion

Measure regional of a set of labeled vectors

Input:

Flag	Type	Description
`--input`	Vects	input vects
`--lookup`	Table	(optional) input lookup table
`--labels`	Vects	(optional) add the following per-vertex labeling to use for computing region statistics

Parameters:

Flag	Type	Default	Description
`--output`	String		output directory
`--name`	String	`name`	(optional) the name of the input data
`--lutname`	String	`name`	(optional) the lookup name field
`--lutindex`	String	`index`	(optional) the lookup index field
`--outname`	String	`name`	(optional) the output name field
`--outvalue`	String	`value`	(optional) the output value field

VectsMeshLaplacian

Filter a vects dataset originating form from a mesh with a laplacian filter

Input:

Flag	Type	Description
`--input`	Vects	the input vector data
`--mesh`	Mesh	the reference mesh (vertices correspond to input)

Parameters:

Flag	Type	Default	Description
`--num`	int	`5`	(optional) a number of iterations
`--lambda`	Double	`0.3`	(optional) the lambda laplacian filtering parameter

Output:

Flag	Type	Description
`--output`	Vects	the output smoothed data

VectsModeMeanShift

Compute the positions of modes of vectors using the mean shift algorithm

Input:

Flag	Type	Description
`--input`	Vects	input vects

Parameters:

Flag	Type	Default	Description
`--bandwidth`	Double	`1.0`	(optional) the spatial bandwidth
`--minshift`	Double	`1.0E-6`	(optional) the error threshold for convergence
`--maxiter`	Integer	`10000`	(optional) the maximum number of iterations

Output:

Flag	Type	Description
`--masses`	Vects	output masses
`--modes`	Vects	output modes

Citation: Comaniciu, D., & Meer, P. (2002). Mean shift: A robust approach toward feature space analysis. IEEE Transactions on pattern analysis and machine intelligence, 24(5), 603-619.

VectsPCA

Perform principal component analysis on vects

Input:

Flag	Type	Description
`--input`	Vects	the input vects

Parameters:

Flag	Type	Default	Description
`--top`	Integer		(optional) none

Output:

Flag	Type	Description
`--mean`	Vects	(optional) the output mean vect
`--comps`	Vects	(optional) the output principal components
`--vals`	Vects	(optional) the output principal values
`--output`	Vects	(optional) the output transformed vects

VectsPrintInfo

Print basic information about vectors

Input:

Flag	Type	Description
`--input`	Vects	the input vects

Parameters:

Flag	Type	Default	Description
`--stats`	flag		(optional) print statistics
`--norm`	flag		(optional) print statistics of vect norms

VectsReduce

Reduce the number of vectors in either a random or systematic way

Input:

Flag	Type	Description
`--input`	Vects	input vects

Parameters:

Flag	Type	Description
`--num`	Integer	(optional) the maxima number of samples
`--fraction`	Double	(optional) the fraction of vects to remove (zero to one)
`--which`	String	(optional) the list of indices to select
`--exclude`	String	(optional) the list of indices to exclude

Output:

Flag	Type	Description
`--output`	Vects	output subsampled vects

VectsRegisterLinear

Estimate a linear transform to register a given pair of vects. You can choose one of several methods to specify the degrees of freedom of the transform and how the transform parameters are estimated

Input:

Flag	Type	Description
`--source`	Vects	input source vects
`--dest`	Vects	input dest vects (should match source)
`--weights`	Vects	(optional) input weights (only available for some methods)

Parameters:

Flag	Type	Default	Description
`--method`	VectsRegisterLinearMethod	`AffineLeastSquares`	(optional) the registration method (each has different degrees of freedom and estimation techniques) (Options: AffineLeastSquares, RigidDualQuaternion)

Output:

Flag	Type	Description
`--output`	Affine	output affine transform mapping source to dest
`--transformed`	Vects	(optional) output transformed source vects (redundant, but useful for validation)

VectsRegisterRigidDualQuaternion

Estimate a rigid transform using the dual quaterionion method. This assumes point-to-point correspondence between vects.

Input:

Flag	Type	Description
`--source`	Vects	input source vects
`--dest`	Vects	input dest vects (should match source)
`--weights`	Vects	(optional) input weights

Output:

Flag	Type	Description
`--output`	Affine	output affine transform mapping source to dest
`--transformed`	Vects	(optional) output transformed source vects (redundant, but useful for validation)

Citation: Walker, Michael W., Lejun Shao, and Richard A. Volz. “Estimating 3-D location parameters using dual number quaternions.” CVGIP: image understanding 54.3 (1991): 358-367.

VectsSample

Sample a volume at a set of points

Input:

Flag	Type	Description
`--input`	Vects	input 3D coordinates
`--volume`	Volume	input volume

Parameters:

Flag	Type	Default	Description
`--interp`	InterpolationType	`Trilinear`	(optional) interpolation method (Options: Nearest, Trilinear, Tricubic, Gaussian, GaussianLocalLinear, GaussianLocalQuadratic)

Output:

Flag	Type	Description
`--output`	Vects	the output samples

VectsSelect

Select a which of vects

Input:

Flag	Type	Description
`--input`	Vects	input vects
`--mask`	Mask	(optional) input mask
`--solids`	Solids	(optional) input solids

Parameters:

Flag	Type	Default	Description
`--or`	flag		(optional) use OR (instead of AND) to combine selections
`--invert`	flag		(optional) invert the selection after combining

Output:

Flag	Type	Description
`--output`	Vects	output selected vects

VectsSpheres

Create spheres from vects

Input:

Flag	Type	Description
`--input`	Vects	input vects

Parameters:

Flag	Type	Default	Description
`--radius`	double	`1.0`	(optional) the sphere radius

Output:

Flag	Type	Description
`--output`	Solids	output solid spheres

VectsSurfaceWarp

Warp vects that are defined on a surface

Input:

Flag	Type	Description
`--input`	Vects	input vects
`--mesh`	Mesh	input mesh

Output:

Flag	Type	Description
`--output`	Vects	output transformed vects

VectsTransform

Transform vects. (note: the order of operations is transpose, flip, swap, perm, affine)

Input:

Flag	Type	Description
`--input`	Vects	input vects
`--affine`	Affine	(optional) apply an affine xfm
`--invaffine`	Affine	(optional) apply an inverse affine xfm
`--deform`	Deformation	(optional) apply a deformation xfm

Parameters:

Flag	Type	Description
`--reverse`	flag	(optional) reverse the order, i.e. compose the affine(deform(x)), whereas the default is deform(affine(x))
`--rows`	flag	(optional) force rows > cols
`--cols`	flag	(optional) force cols > rows
`--transpose`	flag	(optional) transpose
`--subset`	String	(optional) which the coordinates
`--flip`	String	(optional) flip a coodinate (x, y, or z)
`--swap`	String	(optional) swap a pair of coordinates (xy, xz, or yz)
`--perm`	String	(optional) permute by coordinate index, e.g. 1,0,2
`--negate`	flag	(optional) negative the vectors
`--normalize`	flag	(optional) normalize

Output:

Flag	Type	Description
`--output`	Vects	output transformed vects

VolumeBiHistogram

Compute a histogram of a volume

Input:

Flag	Type	Description
`--x`	Volume	the volume for the x-dimension
`--y`	Volume	the volume for the y-dimension
`--mask`	Mask	(optional) an input mask

Parameters:

Flag	Type	Default	Description
`--xbins`	int	`100`	(optional) the number of bins in x
`--ybins`	int	`100`	(optional) the number of bins in y
`--smooth`	Double		(optional) apply smoothing by the given amount
`--exclude`	flag		(optional) exclude counts outside the histogram range
`--xmin`	Double		(optional) the minimum in x
`--ymin`	Double		(optional) the minimum in y
`--xmax`	Double		(optional) the maximum in x
`--ymax`	Double		(optional) the maximum in y

Output:

Flag	Type	Description
`--output`	Volume	output volume
`--breaks`	Volume	(optional) output breaks
`--mapping`	Mask	(optional) output mapping

VolumeBiTensorFit

Fit a bi-tensor volume to a diffusion-weighted MRI.

Input:

Flag	Type	Description
`--input`	Volume	input diffusion-weighted MR volume
`--gradients`	Gradients	the gradients
`--mask`	Mask	(optional) the mask

Parameters:

Flag	Type	Default	Description
`--method`	BiTensorFitType	`Isotropic`	(optional) specify an estimation method (Options: DTI, DTIFWE, Isotropic, FixedIsotropic, BothIsotropic, AlignedZeppelin, Zeppelin, Anisotropic)
`--cost`	CostType	`SE`	(optional) specify a cost function for non-linear fitting (Options: SE, MSE, RMSE, NRMSE, CHISQ, RLL)

Advanced Parameters:

Flag	Type	Default	Description
`--shells`	String		(optional) specify a subset of gradient shells to include (comma-separated list of b-values)
`--which`	String		(optional) specify a subset of gradients to include (comma-separated list of indices starting from zero)
`--exclude`	String		(optional) specify a subset of gradients to exclude (comma-separated list of indices starting from zero)
`--threads`	int	`1`	(optional) the number of threads to use

Output:

Flag	Type	Description
`--output`	Volume	output bitensor volume (name output like *.bti and an directory of volumes will be created)

VolumeBiTensorReduce

Reduce a bitensor volume to a single tensor volume

Input:

Flag	Type	Description
`--input`	Volume	input bitensor volume

Parameters:

Flag	Type	Default	Description
`--fluid`	flag		(optional) return the fluid compartment (default is the tissue compartment)

Advanced Parameters:

Flag	Type	Default	Description
`--threads`	int	`1`	(optional) the number of threads to use

Output:

Flag	Type	Description
`--output`	Volume	output tensor volume

VolumeBiTensorTransform

Spatially transform a bi-tensor volume

Input:

Flag	Type	Description
`--input`	Volume	the input tensor volume
`--reference`	Volume	input reference volume
`--mask`	Mask	(optional) input mask
`--inputMask`	Mask	(optional) use an input mask (defined in the input space)
`--affine`	Affine	(optional) apply an affine xfm
`--invaffine`	Affine	(optional) apply an inverse affine xfm
`--deform`	Deformation	(optional) apply a deformation xfm

Parameters:

Flag	Type	Default	Description
`--reverse`	flag		(optional) reverse the order, i.e. compose the affine(deform(x)), whereas the default is deform(affine(x))
`--reorient`	ReorientationType	`Jacobian`	(optional) specify a reorient method (fs or jac) (Options: FiniteStrain, Jacobian)
`--interp`	KernelInterpolationType	`Trilinear`	(optional) the interpolation type (Options: Nearest, Trilinear, Gaussian)
`--support`	Integer	`3`	(optional) the filter radius in voxels
`--hpos`	Double	`1.0`	(optional) the positional bandwidth in mm
`--log`	flag		(optional) use log estimation

Output:

Flag	Type	Description
`--output`	Volume	the output transformed tensor volume

VolumeBox

Compute the bounding box of a volume

Input:

Flag	Type	Description
`--input`	Volume	input volume

Output:

Flag	Type	Description
`--output`	Solids	output bounding box

VolumeCat

Concatenate two volumes into one

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--cat`	Volume	volume to concatenate
`--mask`	Mask	(optional) input mask

Output:

Flag	Type	Description
`--output`	Volume	output concatenated volume

VolumeCenter

Voxel sizes and position of a volume

Input:

Flag	Type	Description
`--input`	Volume	input Volume

Parameters:

Flag	Type	Default	Description
`--factor`	Double		input voxel dimension scaling factor

Output:

Flag	Type	Description
`--output`	Volume	(optional) output Volume

VolumeConform

Process a volume to conform to a given set of constraints

Input:

Flag	Type	Description
`--input`	Volume	the input volume

Parameters:

Flag	Type	Default	Description
`--maxdi`	double	`1.0`	(optional) the voxel size in i
`--maxdj`	double	`1.0`	(optional) the voxel size in j
`--maxdk`	double	`1.0`	(optional) the voxel size in k
`--interp`	InterpolationType	`Trilinear`	(optional) image interpolation method (Options: Nearest, Trilinear, Tricubic, Gaussian, GaussianLocalLinear, GaussianLocalQuadratic)

Output:

Flag	Type	Description
`--output`	Volume	the output volume

VolumeConvert

Convert a volume to a different format (only useful on command line)

Input:

Flag	Type	Description
`--input`	Volume	input

Parameters:

Flag	Type	Default	Description
`--proto`	flag		(optional) only copy the structure, not the intensities

Output:

Flag	Type	Description
`--output`	Volume	output

VolumeCreate

Create a volume based on user specified parameters

Input:

Flag	Type	Description
`--reference`	Volume	(optional) an optional reference volume for setting the voxel grid

Parameters:

Flag	Type	Default	Description
`--channels`	int	`1`	(optional) the number of channels
`--deltax`	double	`1.0`	(optional) voxel spacing in x
`--deltay`	double	`1.0`	(optional) voxel spacing in y
`--deltaz`	double	`1.0`	(optional) voxel spacing in z
`--numx`	int	`128`	(optional) number of voxels in x
`--numy`	int	`128`	(optional) number of voxels in y
`--numz`	int	`128`	(optional) number of voxels in z
`--startx`	double	`0.0`	(optional) starting position in x
`--starty`	double	`0.0`	(optional) starting position in y
`--startz`	double	`0.0`	(optional) starting position in z
`--value`	double	`0.0`	(optional) constant value
`--grid`	flag		(optional) draw a grid
`--gridSpace`	int	`20`	(optional) the grid spacing in voxels (number of voxels between grid lines)
`--gridThick`	int	`0`	(optional) the grid thickness in voxels (diameter will be 2 * n + 1)
`--gridValue`	int	`1`	(optional) the grid intensity

Output:

Flag	Type	Description
`--output`	Volume	output volume

VolumeCrop

Crop a volume down to a smaller volume (only one criteria per run)

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mask`	Mask	(optional) a mask
`--solids`	Solids	(optional) some soids

Parameters:

Flag	Type	Default	Description
`--range`	String		(optional) a range specification, e.g. start:end,start:end,start:end
`--thresh`	Double		(optional) crop out the background with a given threshold
`--invert`	flag		(optional) invert the selection
`--even`	flag		(optional) ensure the volume has even dimensions
`--pad`	int	`0`	(optional) a padding size in voxels

Output:

Flag	Type	Description
`--output`	Volume	the output volume

VolumeDeformationCompose

Compose a deformation field with an affine transform

Input:

Flag	Type	Description
`--affine`	Affine	an affine transform
`--deform`	Volume	(optional) an deform deformation field
`--reference`	Volume	(optional) a reference image

Parameters:

Flag	Type	Default	Description
`--invert`	flag		(optional) invert the affine transform
`--reverse`	flag		(optional) reverse the order of the transforms

Output:

Flag	Type	Description
`--output`	Volume	output

VolumeDifferenceMap

Summarize the difference between two image volumes

Input:

Flag	Type	Description
`--left`	Volume	input left volume
`--right`	Volume	input right volume
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--prefix`	String	``	(optional) a prefix for the output names

Output:

Flag	Type	Description
`--output`	Table	the table

VolumeDownsample

Downsample a volume. Unlike VolumeZoom, this includes a prefiltering step with a triangle filter to reduce alias artifact

Input:

Flag	Type	Description
`--input`	Volume	the input volume

Parameters:

Flag	Type	Default	Description
`--factor`	double	`2.0`	(optional) an downsampling scaling factor
`--threads`	Integer	`3`	(optional) the number of threads in the pool

Output:

Flag	Type	Description
`--output`	Volume	the output volume

VolumeDwiAdc

Compute the apparent mri coefficient (ADC) of the mri signal. The default output is the mean ADC, but per-gradient outputs can also be computed

Input:

Flag	Type	Description
`--input`	Volume	the input diffusion-weighted MR volume
`--gradients`	Gradients	the input gradients
`--mask`	Mask	(optional) the input mask

Parameters:

Flag	Type	Default	Description
`--component`	flag		(optional) compute the ADC for each gradient, otherwise the average will be computed

Output:

Flag	Type	Description
`--output`	Volume	the output ADC volume

VolumeDwiAverage

Average subvolumes from diffusion MRI. This is often used to improve the SNR when the scan includes repeats

Input:

Flag	Type	Description
`--dwi`	Volume	the input diffusion-weighted MR volume
`--gradients`	Gradients	the input gradients (must match input DWI)

Parameters:

Flag	Type	Default	Description
`--average`	String		(optional) a file or comma-separated list of integers specifying how the data should be grouped, e.g. 1,1,1,2,2,2,3,3,3,…

Output:

Flag	Type	Description
`--outputDwi`	Volume	the output dwi volume
`--outputGradients`	Gradients	(optional) the output gradients

VolumeDwiBaseline

Extract baseline signal statistics from a diffusion-weighted MR volume

Input:

Flag	Type	Description
`--input`	Volume	the input diffusion-weighted MR volume
`--gradients`	Gradients	the input gradients
`--mask`	Mask	(optional) the input mask

Output:

Flag	Type	Description
`--mean`	Volume	(optional) the output mean baseline signal
`--median`	Volume	(optional) the output median baseline signal
`--var`	Volume	(optional) the output variance of baseline signal (only meaningful if there are multiple baselines)
`--std`	Volume	(optional) the output standard deviation of baseline signal (only meaningful if there are multiple baselines)
`--cat`	Volume	(optional) the output complete set of baseline signals
`--drift`	Volume	(optional) the output signal drift estimates (slope, stderr, tstat, pval, sig) measured by percentage change

Citation: Vos, Sjoerd B., et al. “The importance of correcting for signal drift in diffusion MRI.” Magnetic resonance in medicine 77.1 (2017): 285-299.

VolumeDwiCleanMask

Clean a brain mask to remove background voxels

Input:

Flag	Type	Description
`--input`	Volume	the input diffusion-weighted MR volume
`--gradients`	Gradients	the input gradients (must match input DWI)
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--depth`	int	`2`	(optional) cleaning depth from the boundary
`--threshold`	Double	`1.5`	(optional) the threshold (multiplier for inter-quartile range)
`--nomode`	flag		(optional) skip mode filtering
`--threads`	Integer	`1`	(optional) the number of threads to use

Output:

Flag	Type	Description
`--output`	Mask	the output mask

VolumeDwiCorrectDrift

Correct for signal drift in a diffusion-weighted MR volume using a polynomial model

Input:

Flag	Type	Description
`--input`	Volume	the input diffusion-weighted MR volume
`--gradients`	Gradients	the input gradients
`--mask`	Mask	(optional) the input mask

Parameters:

Flag	Type	Default	Description
`--global`	flag		(optional) use global drift estimation
`--local`	flag		(optional) use local drift estimation
`--iso`	flag		(optional) use isotropic drift estimation
`--blend`	flag		(optional) use blended drift estimation
`--order`	int	`2`	(optional) the order of the polynomial model

Output:

Flag	Type	Description
`--output`	Volume	the output corrected dwi

Citation: Vos, Sjoerd B., et al. “The importance of correcting for signal drift in diffusion MRI.” Magnetic resonance in medicine 77.1 (2017): 285-299.

VolumeDwiEstimateNoise

Estimate the noise parameter from the baselines of a DWI

Input:

Flag	Type	Description
`--input`	Volume	input dwi
`--gradients`	Gradients	input gradients
`--mask`	Mask	(optional) input mask

Output:

Flag	Type	Description
`--output`	Volume	output error volume

VolumeDwiFeature

Compute features of the the diffusion weighted signal. These features are statistical summaries of the signal within and across shells (depending on the method), mostly avoiding any modeling assumptions

Input:

Flag	Type	Description
`--input`	Volume	the input diffusion-weighted MR volume
`--gradients`	Gradients	the input gradients
`--mask`	Mask	(optional) the input mask

Parameters:

Flag	Type	Default	Description
`--feature`	VolumeDwiFeatureType	`AnisoCoeffVar`	(optional) the method for computing anisotropy (Options: Attenuation, AnisoCoeffVar, AnisoStd, AnisoMu, SphericalMean, SphericalMeanNorm, SphericalMeanADC, SphericalStd, NoiseStd, NoiseCoeffVar)

Output:

Flag	Type	Description
`--output`	Volume	the output anisotropy volume

VolumeDwiNormalize

normalize a mri weighted image volume by the baseline signal

Input:

Flag	Type	Description
`--input`	Volume	the input diffusion-weighted MR volume
`--gradients`	Gradients	the input gradients
`--mask`	Mask	(optional) the input mask

Parameters:

Flag	Type	Description
`--grouping`	String	(optional) a grouping of scans with similar TE/TR (otherwise all scans are assumed to be part of one group)
`--unit`	flag	(optional) normalize the signal to the unit interval (divide by average baseline by voxel)
`--mean`	Double	(optional) normalize the signal to have a given mean value across the entire volume

Output:

Flag	Type	Description
`--output`	Volume	the output baseline volume

VolumeDwiReduce

Reduce the number of mri samples in a mri weighted image

Input:

Flag	Type	Description
`--dwi`	Volume	the input diffusion-weighted MR volume
`--gradients`	Gradients	the input gradients (must match input DWI)

Parameters:

Flag	Type	Description
`--shells`	String	(optional) include only specific shells
`--which`	String	(optional) include only specific gradients (comma separated zero-based indices)
`--exclude`	String	(optional) exclude specific gradients (comma separated zero-based indices)
`--bscale`	Double	(optional) scale the baseline signal by the given amount (this is very rarely necessary)

Output:

Flag	Type	Description
`--outputDwi`	Volume	the output dwi volume
`--outputGradients`	Gradients	(optional) the output gradients

VolumeDwiResampleGP

Resample a diffusion-weighted MR volume to have a different set of gradients (arbitrary b-vectors and b-values)

Input:

Flag	Type	Description
`--input`	Volume	the input diffusion-weighted MR volume
`--gradients`	Gradients	the input gradients (must match input DWI)
`--reference`	Gradients	the gradients used for resampling
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--lambda`	Double	`0.1`	(optional) the lambda parameter (controls smoothness)
`--alpha`	Double	`1.0`	(optional) the alpha parameter (controls gradient direction scaling)
`--beta`	Double	`1.0`	(optional) the beta parameter (controls gradient strength scaling)
`--threads`	Integer	`1`	(optional) the number of threads to use

Output:

Flag	Type	Description
`--output`	Volume	the output resampled diffusion-weighted MR volume (will match reference gradients)

Citation: Andersson, J. L., & Sotiropoulos, S. N. (2015). Non-parametric representation and prediction of single-and multi-shell diffusion-weighted MRI data using Gaussian processes. NeuroImage, 122, 166-176.

VolumeDwiResampleOutlierGP

Detect and replace outliers of a diffusion-weighted MR volume using Gaussian Process regression. This first detects outliers using a very smooth GP model and then replaces only those outliers using a more rigid GP model

Input:

Flag	Type	Description
`--input`	Volume	the input diffusion-weighted MR volume
`--gradients`	Gradients	the input gradients (must match input DWI)
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--outlier`	Double	`0.35`	(optional) the threshold for outlier detection. this is the fractional change in single value from the GP prediction to qualify as an outlier
`--include`	Double	`0.75`	(optional) the minimum fraction of gradient directions to use for outlier replacement. if more than this fraction are considered inliers, then interpolation will be used
`--lambdaDetect`	Double	`1.0`	(optional) the lambda parameter for detecting outliers (controls smoothness)
`--lambdaPredict`	Double	`1.0`	(optional) the lambda parameter for replacing outliers (controls smoothness)
`--resample`	flag		(optional) resample all signal values with reduced GP (default will only resample outliers)
`--alpha`	Double	`1.0`	(optional) the alpha parameter (controls gradient direction scaling)
`--beta`	Double	`1.0`	(optional) the beta parameter (controls gradient strength scaling)
`--threads`	Integer	`1`	(optional) the number of threads to use

Output:

Flag	Type	Description
`--output`	Volume	the output resampled diffusion-weighted MR volume (will match reference gradients)

Citation: Andersson, J. L., & Sotiropoulos, S. N. (2015). Non-parametric representation and prediction of single-and multi-shell diffusion-weighted MRI data using Gaussian processes. NeuroImage, 122, 166-176.

VolumeDwiResampleSpherical

Resample a diffusion-weighted MR volume to have a different set of gradients (single shell only)

Input:

Flag	Type	Description
`--input`	Volume	the input diffusion-weighted MR volume
`--source`	Gradients	the (original) source gradients
`--dest`	Vects	the destination gradient directions
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--filter`	String	`linear`	(optional) specify a filtering method (linear, local, or global)
`--kappa`	Double	`5.0`	(optional) the lambda parameter
`--lambda`	Double	`0.1`	(optional) the lambda parameter
`--sigma`	Double	`20.0`	(optional) the sigma parameter
`--adaptive`	flag		(optional) use adaptive resampling

Output:

Flag	Type	Description
`--output`	Volume	the output resampled diffusion-weighted MR volume

VolumeDwiSphericalMean

Compute the spherical mean for each shell.

Input:

Flag	Type	Description
`--dwi`	Volume	the dwi diffusion-weighted MR volume
`--gradients`	Gradients	the (original) source gradients
`--mask`	Mask	(optional) a mask

Output:

Flag	Type	Description
`--outputDwi`	Volume	the output resampled diffusion-weighted MR volume
`--outputBvals`	Vects	the output b-values

VolumeDwiSubsample

Subsample a mri weighted volume by removing channels to maximize the separation of gradient directions. This is currently optimized for single shell data

Input:

Flag	Type	Description
`--indwi`	Volume	the input diffusion-weighted MR volume
`--ingrad`	Gradients	the input gradients

Parameters:

Flag	Type	Default	Description
`--nums`	int	`1`	(optional) the number of baseline channels to keep
`--numd`	int	`12`	(optional) the number of diffusion-weighted channels to keep

Output:

Flag	Type	Description
`--outdwi`	Volume	the output diffusion-weighted MR volume
`--outgrad`	Gradients	the output gradients

VolumeEnhanceContrast

enhance the intensity contrast of a given volume. The output will have a range of zero to one.

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mask`	Mask	(optional) input mask

Parameters:

Flag	Type	Default	Description
`--type`	VolumeEnhanceContrastType	`Histogram`	(optional) the type of contrast enhancement (Options: Histogram, Ramp, RampGauss, Mean, None)
`--squeeze`	VolumeEnhanceContrastSqueeze	`None`	(optional) the type of squeezing (Options: Square, Root, Sine, SquineLow, SquineHigh, None)
`--bins`	int	`1024`	(optional) the number of histogram bins
`--gauss`	double	`3.0`	(optional) the Gaussian bandwidth
`--scale`	double	`1.0`	(optional) the intensity scaling
`--smooth`	Double		(optional) smooth the histogram by adding the given proportion of the total (reduces effect of outliers)
`--nobg`	flag		(optional) remove background voxels
`--invert`	flag		(optional) invert the intensities on a unit interval
`--thresh`	double	`1.0E-6`	(optional) specify a threshold for background removal

Output:

Flag	Type	Description
`--output`	Volume	output enhanced image

VolumeEstimateLookup

Compute a histogram of a volume

Input:

Flag	Type	Description
`--from`	Volume	the volume for the x-dimension
`--to`	Volume	the volume for the y-dimension
`--mask`	Mask	(optional) an input mask

Parameters:

Flag	Type	Default	Description
`--bins`	int	`100`	(optional) the number of bins in x
`--xmin`	Double		(optional) the minimum in x
`--xmax`	Double		(optional) the maximum in x
`--inputField`	String	`input`	(optional) the name field name for the input value
`--outputField`	String	`output`	(optional) the name field name for the output value

Output:

Flag	Type	Description
`--output`	Table	output table
`--breaks`	Volume	(optional) output breaks

VolumeExpDecayError

Synthesize a volume from exp decay parameters

Input:

Flag	Type	Description
`--input`	Volume	input exp decay sample volume
`--varying`	Vects	the varying parameters
`--model`	Volume	the exponential decay model parameter volume
`--mask`	Mask	(optional) input mask

Parameters:

Flag	Type	Default	Description
`--method`	String	`nrmse`	(optional) the type of error metric (me, nme, sse, nsse, mse, nmse, rmse, nrmse)

Output:

Flag	Type	Description
`--output`	Volume	output error

VolumeExpDecayFit

Fit an exponential decay model to volumetric data: y = alpha * exp(-beta * x)

Input:

Flag	Type	Description
`--input`	Volume	the input dwi
`--varying`	Vects	(optional) the varying parameters values used for fitting, if not provided the start and step parameters are used instead
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--method`	String	`wlls`	(optional) the method for fitting (lls, wlls, nlls)
`--start`	Double	`1.0`	(optional) the starting echo time (not used if you provide a varying input)
`--step`	Double	`1.0`	(optional) the spacing between echo times (not used if you provide a varying input)
`--minAlpha`	Double	`0.0`	(optional) the minimum alpha
`--minBeta`	Double	`0.0`	(optional) the minimum beta
`--thresh`	Double		(optional) apply a threshold to the input image, e.g. remove zero values
`--shrinkage`	flag		(optional) apply shrinkage regularization for low SNR regions
`--shrinkSmooth`	Integer	`5`	(optional) the amount of smoothing to apply
`--shrinkSnrMax`	Double	`7.0`	(optional) the maximum shrinkage snr
`--shrinkSnrMin`	Double	`5.0`	(optional) the minimum shrinkage snr
`--threads`	Integer	`1`	(optional) the mynumber of threads in the pool

Advanced Parameters:

Flag	Type	Description
`--which`	String	(optional) specify a subset of data to include (comma-separated list of indices starting from zero)
`--exclude`	String	(optional) specify a subset of data to exclude (comma-separated list of indices starting from zero)
`--select`	String	(optional) specify a subset of values to include (as opposed to indices)
`--skipFirstThresh`	Integer	(optional) skip the first value if there are more than the given number of values (this is for an unusual edge case)

Output:

Flag	Type	Description
`--output`	Volume	(optional) the output exp decay model volume
`--outputAlpha`	Volume	(optional) the output exp decay alpha parameter
`--outputBeta`	Volume	(optional) the output exp decay beta parameter
`--outputError`	Volume	(optional) the output exp decay error
`--outputResiduals`	Volume	(optional) the output exp decay residuals
`--outputSnr`	Volume	(optional) the output exp decay SNR map

VolumeExpDecaySynth

Synthesize a volume from exp decay parameters

Input:

Flag	Type	Description
`--input`	Volume	input exp decay volume
`--varying`	Vects	the varying parameters
`--mask`	Mask	(optional) input mask

Output:

Flag	Type	Description
`--output`	Volume	predicted output

VolumeExpRecoveryError

Synthesize a volume from exp recovery parameters

Input:

Flag	Type	Description
`--input`	Volume	input exp recovery sample volume
`--varying`	Vects	the varying parameters
`--model`	Volume	the exponential recovery model parameter volume
`--mask`	Mask	(optional) input mask

Parameters:

Flag	Type	Default	Description
`--method`	String	`nrmse`	(optional) the type of error metric (me, nme, sse, nsse, mse, nmse, rmse, nrmse)

Output:

Flag	Type	Description
`--output`	Volume	output error

VolumeExpRecoveryFit

Fit an exponential recovery model to volumetric data: y = alpha * exp(-beta * x)

Input:

Flag	Type	Description
`--input`	Volume	the input dwi
`--varying`	Vects	the varying parameters values used for fitting
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--threads`	Integer	`1`	(optional) the number of threads in the pool

Output:

Flag	Type	Description
`--output`	Volume	the output exp recovery model volume

VolumeExpRecoverySynth

Synthesize a volume from exp recovery parameters

Input:

Flag	Type	Description
`--input`	Volume	input exp recovery volume
`--varying`	Vects	the varying parameters
`--mask`	Mask	(optional) input mask

Output:

Flag	Type	Description
`--output`	Volume	predicted output

VolumeExtrema

Compute the local extrema of a volume

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--channel`	int	`0`	(optional) the volume channel
`--minima`	flag		(optional) find the minima
`--maxima`	flag		(optional) find the maxima
`--element`	String	`cross`	(optional) specify an element

Output:

Flag	Type	Description
`--output`	Mask	output mask

VolumeFibersError

Compute error metrics between a ground truth and test fibers volume

Input:

Flag	Type	Description
`--truth`	Volume	the truth fibers volume
`--test`	Volume	the test fibers volume
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--thresh`	double	`0.05`	(optional) a threshold for compartment existence

Output:

Flag	Type	Description
`--missing`	Volume	(optional) output measuring number of missing compartment error
`--extra`	Volume	(optional) output measuring number of extra compartment error
`--linehaus`	Volume	(optional) output measuring the hausdorff angular error
`--linetotal`	Volume	(optional) output measuring the total angular error
`--frachaus`	Volume	(optional) output measuring the hausdorff fraction error
`--fractotal`	Volume	(optional) output measuring the total fraction error
`--fraciso`	Volume	(optional) output measuring the isotropic fraction error

VolumeFibersFilter

Add orientation and volume fraction noise to a fibers volume

Input:

Flag	Type	Description
`--input`	Volume	input fibers volume
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--base`	Double	`1.0`	(optional) the fraction gain
`--frac`	Double	`2.0`	(optional) the fraction gain
`--angle`	Double	`1.0`	(optional) the angle gain
`--align`	Double	`2.0`	(optional) the align gain

Output:

Flag	Type	Description
`--output`	Volume	output noisy fibers volume

VolumeFibersFit

Fit a fibers volume using a multi-stage procedure

Input:

Flag	Type	Description
`--input`	Volume	input diffusion-weighted MR volume
`--gradients`	Gradients	the gradients
`--mask`	Mask	(optional) the mask

Parameters:

Flag	Type	Default	Description
`--round`	Integer		(optional) specify rounding factor for the gradients
`--threads`	Integer	`1`	(optional) the number of threads in the pool
`--columns`	flag		(optional) use fine-grained multi-threading
`--minfrac`	double	`0.01`	(optional) the minimum volume fraction
`--comps`	int	`3`	(optional) the maximum number of fiber compartments to extract
`--points`	Integer	`256`	(optional) the number of points used for peak extraction
`--cluster`	double	`30.0`	(optional) the angle for peak clustering
`--peak`	PeakMode	`Sum`	(optional) the statistic for aggregating peaks (Options: Sum, Mean, Max)
`--dmax`	double	`0.003`	(optional) the maximum diffusivity for MCSMT
`--maxiters`	int	`1500`	(optional) the maximum number of iterations for MCSMT
`--diffinit`	DiffInit	`Best`	(optional) specify a method for initializing diffusivity (Options: Tensor, Fixed, Best)
`--method`	Method	`RLD`	(optional) specify an orientation estimation method (Options: CSD, RLD)
`--rldIters`	int	`500`	(optional) the number of iterations for RLD
`--rldAlpha`	double	`0.0017`	(optional) the alpha parameter for RLD
`--rldBeta`	double	`0.0`	(optional) the beta parameter for RLD
`--csdOrder`	Integer	`8`	(optional) specify the maximum spherical harmonic order for CSD
`--csdAxial`	double	`0.0017`	(optional) the axial fiber response for CSD
`--csdRadial`	double	`1.2E-4`	(optional) the radial fiber response for CSD
`--csdTau`	double	`0.1`	(optional) the tau parameter for CSD
`--csdLambda`	double	`0.2`	(optional) the lambda parameter for CSD
`--csdIters`	int	`50`	(optional) the number of iterations for CSD

Advanced Parameters:

Flag	Type	Default	Description
`--shells`	String		(optional) specify a subset of gradient shells to include (comma-separated list of b-values)
`--which`	String		(optional) specify a subset of gradients to include (comma-separated list of indices starting from zero)
`--exclude`	String		(optional) specify a subset of gradients to exclude (comma-separated list of indices starting from zero)
`--dperp`	Double		(optional) use the givel fraction of axial diffusivity when fitting fiber volume fractions
`--dfix`	Double	`0.00125`	(optional) use the given fixed axial diffusivity when fitting fiber volume fractions
`--tort`	flag		(optional) use a tortuosity model (otherwise the extra-cellular diffusivity is matched to the intra)
`--restarts`	Integer	`1`	(optional) use the given fixed axial diffusivity when fitting fiber volume fractions
`--nosmt`	flag		(optional) skip SMT estimation (for multishell data only)
`--modeSingle`	Mode	`FracSumDiffMultistage`	(optional) specify an parameter estimation mode for single shell analysis (Options: Fracs, FracsFixedSum, FracsDiff, FracSum, FracSumDiff, Diff, FracSumDiffMultistage, FracsDiffMultistage)
`--modeMulti`	Mode	`FracsFixedSum`	(optional) specify an parameter estimation mode for single shell analysis (Options: Fracs, FracsFixedSum, FracsDiff, FracSum, FracSumDiff, Diff, FracSumDiffMultistage, FracsDiffMultistage)

Output:

Flag	Type	Description
`--output`	Volume	output fibers volume

VolumeFibersNoise

Add orientation and volume fraction noise to a fibers volume

Input:

Flag	Type	Description
`--input`	Volume	input fibers volume
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--line`	Double		(optional) the sigma of the orientation noise
`--frac`	Double		(optional) the sigma of the volume fraction noise

Output:

Flag	Type	Description
`--output`	Volume	output noisy fibers volume

VolumeFibersPhantomCrossing

Create a benchmark fibers phantom

Parameters:

Flag	Type	Default	Description
`--size`	int	`50`	(optional) the size of the phantom
`--fracPrimary`	double	`0.4`	(optional) volume fraction of the primary bundle
`--fracSecondary`	double	`0.4`	(optional) volume fraction of the secondary bundle
`--radiusPrimary`	double	`0.4`	(optional) the relative radius of the primary bundle (0 to 1)
`--radiusSecondary`	double	`0.2`	(optional) the relative radius of the secondary bundle (0 to 1)
`--angle`	double	`45.0`	(optional) the angle between the primary and secondary bundles
`--noiseAngle`	double	`5.0`	(optional) the amount of noise added to the compartment fiber orientations
`--noiseFraction`	double	`0.05`	(optional) the amount of noise added to the compartment volume fraction

Output:

Flag	Type	Description
`--output`	Volume	the synthesized output fibers
`--outputBundle`	Mask	(optional) the output bundle mask
`--outputEnd`	Mask	(optional) the output end mask

VolumeFibersPick

Project fibers onto a reference volume

Input:

Flag	Type	Description
`--input`	Volume	the input fibers to pick
`--reference`	Volume	the reference vectors
`--mask`	Mask	(optional) a mask of the input image
`--deform`	Deformation	(optional) a deformation from the input to the reference

Parameters:

Flag	Type	Default	Description
`--thresh`	double	`0.05`	(optional) a threshold for picking
`--threads`	int	`1`	(optional) the number of threads

Output:

Flag	Type	Description
`--output`	Volume	the output fibers

VolumeFibersProject

Project fibers onto a reference volume

Input:

Flag	Type	Description
`--input`	Volume	the input fibers to project
`--reference`	Volume	the reference fibers (may be deformed from another space)
`--mask`	Mask	(optional) a mask of the input image
`--deform`	Deformation	(optional) a deformation from the input to the reference

Parameters:

Flag	Type	Default	Description
`--thresh`	double	`0.01`	(optional) a threshold for compartment existence
`--keep`	flag		(optional) keep the reference fiber orientations
`--angle`	Double		(optional) the maximum angle for matching
`--presmooth`	Double		(optional) apply fiber smoothing before projection with the given bandwidth
`--smooth`	flag		(optional) apply fiber smoothing after projection
`--threads`	int	`1`	(optional) the number of threads

Advanced Parameters:

Flag	Type	Default	Description
`--soft`	flag		(optional) use soft projection with angular smoothing
`--soften`	Double	`0.1`	(optional) use the given soft smoothing angular bandwidth (zero to one, where greater is more smoothing)
`--deviation`	flag		(optional) save the angular deviation to the fiber statistic field of the output
`--hpos`	Double		(optional) apply smoothing with the given amount (bandwidth in mm) (default is largest voxel dimension)
`--mix`	Double		(optional) smoothly mix reference and the input voxel fiber orientations (0 is all input, 1 is all reference)
`--support`	int	`3`	(optional) the smoothing filter radius in voxels

Output:

Flag	Type	Description
`--output`	Volume	the output fibers

VolumeFibersPrune

Prune outlier fibers

Input:

Flag	Type	Description
`--input`	Volume	the input fibers
`--mask`	Mask	(optional) a mask of the input image

Parameters:

Flag	Type	Description
`--normalize`	flag	(optional) globally normalize the volume fractions to be in a unit range
`--min`	Double	(optional) a minimum volume fraction
`--thresh`	Double	(optional) a threshold angle for pruning (in degrees)

Output:

Flag	Type	Description
`--output`	Volume	the output fibers

VolumeFibersSmooth

Smooth a fibers volume

Input:

Flag	Type	Description
`--input`	Volume	the input fibers volume
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--hpos`	Double	`1.0`	(optional) the positional bandwidth in mm (negative value will use the voxel size, zero will skip smoothing)
`--support`	Integer	`3`	(optional) the filter radius in voxels
`--comps`	int	`3`	(optional) a maxima number of fiber compartments
`--threads`	Integer	`1`	(optional) the number of threads in the pool

Advanced Parameters:

Flag	Type	Default	Description
`--hsig`	Double		(optional) the baseline signal adaptive bandwidth
`--hsigrel`	flag		(optional) treat hsig as a fraction of the mean baseline signal (inside the mask)
`--hfrac`	Double		(optional) the fraction adaptive bandwidth
`--hdiff`	Double		(optional) the diffusivity adaptive bandwidth
`--hdir`	Double		(optional) the fiber adaptive bandwidth
`--min`	double	`0.01`	(optional) a minima volume fraction
`--lambda`	double	`0.99`	(optional) a data adaptive threshold
`--restarts`	int	`2`	(optional) a number of restarts
`--pass`	flag		(optional) pass through the data without smoothing

Output:

Flag	Type	Description
`--output`	Volume	the output fibers volume

Citation: Cabeen, R. P., Bastin, M. E., & Laidlaw, D. H. (2016). Kernel regression estimation of fiber orientation mixtures in mri MRI. NeuroImage, 127, 158-172.

VolumeFibersTransform

Spatially transform a fibers volume

Input:

Flag	Type	Description
`--input`	Volume	the input fibers volume
`--reference`	Volume	input reference volume
`--mask`	Mask	(optional) input mask
`--inputMask`	Mask	(optional) use an input mask (defined in the input space)
`--affine`	Affine	(optional) apply an affine xfm
`--invaffine`	Affine	(optional) apply an inverse affine xfm
`--deform`	Deformation	(optional) apply a deformation xfm

Parameters:

Flag	Type	Default	Description
`--reverse`	flag		(optional) reverse the order, i.e. compose the affine(deform(x)), whereas the default is deform(affine(x))
`--reorientation`	ReorientationType	`Jacobian`	(optional) specify a reorient method (Options: FiniteStrain, Jacobian)
`--estimation`	EstimationType	`Match`	(optional) the estimation type (Options: Match, Rank)
`--selection`	SelectionType	`Adaptive`	(optional) the selection type (Options: Max, Fixed, Linear, Adaptive)
`--interp`	KernelInterpolationType	`Trilinear`	(optional) the interpolation type (Options: Nearest, Trilinear, Gaussian)
`--comps`	int	`3`	(optional) a maxima number of fiber compartments
`--support`	Integer	`3`	(optional) the filter radius in voxels
`--hpos`	Double	`1.0`	(optional) the positional bandwidth in mm
`--min`	double	`0.01`	(optional) a minima volume fraction
`--lambda`	double	`0.99`	(optional) a data adaptive threshold
`--threads`	int	`1`	(optional) the number of threads

Output:

Flag	Type	Description
`--output`	Volume	the output transformed volume

Citation: Cabeen, R. P., Bastin, M. E., & Laidlaw, D. H. (2016). Kernel regression estimation of fiber orientation mixtures in mri MRI. NeuroImage, 127, 158-172.

VolumeFibersZoom

Zoom a fibers volume

Input:

Flag	Type	Description
`--input`	Volume	the input fibers volume
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--factor`	double	`2.0`	(optional) a zooming factor
`--isotropic`	Double		(optional) zoom to a given isotropic voxel size (not by a factor)
`--estimation`	EstimationType	`Match`	(optional) the estimation type (Options: Match, Rank)
`--selection`	SelectionType	`Linear`	(optional) the selection type (Options: Max, Fixed, Linear, Adaptive)
`--interp`	KernelInterpolationType	`Trilinear`	(optional) the interpolation type (Options: Nearest, Trilinear, Gaussian)
`--comps`	int	`3`	(optional) a maxima number of fiber compartments
`--support`	Integer	`3`	(optional) the filter radius in voxels
`--hpos`	Double	`1.0`	(optional) the positional bandwidth in mm
`--min`	double	`0.01`	(optional) a minima volume fraction
`--lambda`	double	`0.99`	(optional) a data adaptive threshold

Output:

Flag	Type	Description
`--output`	Volume	the output fibers volume

Citation: Cabeen, R. P., Bastin, M. E., & Laidlaw, D. H. (2016). Kernel regression estimation of fiber orientation mixtures in mri MRI. NeuroImage, 127, 158-172.

VolumeFilterBilateral

Filter a volume with a bilateral filter

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mask`	Mask	(optional) input mask

Parameters:

Flag	Type	Default	Description
`--channel`	Integer		(optional) volume channel (default applies to all)
`--hpos`	Double	`1.0`	(optional) positional bandwidth
`--hval`	Double		(optional) data adaptive bandwidth
`--support`	int	`3`	(optional) filter radius in voxels (filter will be 2 * support + 1 in each dimension)
`--iterations`	int	`1`	(optional) number of repeats

Output:

Flag	Type	Description
`--output`	Volume	output volume

Citation: Elad, M. (2002). On the origin of the bilateral filter and ways to improve it. IEEE Transactions on image processing, 11(10), 1141-1151.

VolumeFilterDoG

Filter a volume using a Gaussian kernel

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mask`	Mask	(optional) input mask

Parameters:

Flag	Type	Default	Description
`--support`	int	`3`	(optional) filter support (filter will be 2 * support + 1 voxels in each dimension)
`--low`	double	`1.0`	(optional) the low smoothing level
`--high`	double	`2.0`	(optional) the low smoothing level
`--num`	int	`1`	(optional) number of applications
`--threads`	int	`1`	(optional) number of threads
`--preserve`	flag		(optional) preserve un-masked values through the filter

Output:

Flag	Type	Description
`--output`	Volume	output mask

VolumeFilterFrangi

Filter a volume using a Frangi filter. This extracts tubular structures (scale level is the sigma parameter of a Gaussian in mm)

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mask`	Mask	(optional) input mask

Parameters:

Flag	Type	Default	Description
`--support`	int	`3`	(optional) filter support (filter will be 2 * support + 1 voxels in each dimension)
`--low`	double	`1.0`	(optional) the low scale level
`--high`	double	`5.0`	(optional) the high scale level
`--scales`	int	`5`	(optional) the number of scale samples
`--alpha`	double	`0.5`	(optional) the alpha Frangi parameter
`--beta`	double	`0.5`	(optional) the beta Frangi parameter
`--gamma`	double	`300.0`	(optional) the gamma Frangi parameter for 3D structures
`--gammaPlanar`	double	`15.0`	(optional) the gamma Frangi parameter for 2D structures
`--threads`	int	`1`	(optional) number of threads
`--dark`	flag		(optional) use detect dark tubes instead of bright tubes
`--sobel`	flag		(optional) use a sobel operator (default is central finite difference)
`--full`	flag		(optional) return the full scale space (default is maximum)
`--pass`	flag		(optional) pass un-masked values through the filter

Advanced Parameters:

Flag	Type	Default	Description
`--num`	int	`1`	(optional) number of smoothing iterations

Output:

Flag	Type	Description
`--output`	Volume	output filter response
`--outputScale`	Volume	(optional) output scale of the tubular structure

Citation: Frangi, Alejandro F., et al. “Multiscale vessel enhancement filtering.” International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer, Berlin, Heidelberg, 1998.

VolumeFilterGaussian

Filter a volume using a Gaussian kernel

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mask`	Mask	(optional) input mask

Parameters:

Flag	Type	Default	Description
`--support`	int	`3`	(optional) filter support (filter will be 2 * support + 1 voxels in each dimension)
`--sigma`	Double	`1.0`	(optional) the smoothing level
`--num`	int	`1`	(optional) number of applications
`--threads`	int	`1`	(optional) number of threads
`--full`	flag		(optional) use a full convolution filter (otherwise separate filters are used)
`--pass`	flag		(optional) pass un-masked values through the filter
`--channel`	Integer		(optional) the volume channel (default applies to all)

Output:

Flag	Type	Description
`--output`	Volume	output filtered volume

VolumeFilterGradient

Filter a volume to compute its Hessian

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mask`	Mask	(optional) input mask

Parameters:

Flag	Type	Default	Description
`--threads`	int	`1`	(optional) number of threads
`--sobel`	flag		(optional) use a sobel operator (default is central finite difference)
`--mag`	flag		(optional) return the gradient magnitude

Output:

Flag	Type	Description
`--output`	Volume	output mask

VolumeFilterHessian

Filter a volume to compute its Hessian

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mask`	Mask	(optional) input mask

Parameters:

Flag	Type	Default	Description
`--threads`	int	`1`	(optional) number of threads
`--sobel`	flag		(optional) use a sobel operator (default is central finite difference)
`--mode`	VolumeFilterHessianMode	`Matrix`	(optional) return the given output mode (Options: Matrix, Eigen, Determ, Norm, Westin, Spherical, Linear, Planar, Ridge, Blob, DarkBlob, LightBlob)

Output:

Flag	Type	Description
`--output`	Volume	output mask

VolumeFilterLaplacian

Filter a volume using a Laplacian kernel

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mask`	Mask	(optional) input mask

Parameters:

Flag	Type	Default	Description
`--support`	int	`3`	(optional) filter support (filter will be 2 * support + 1 voxels in each dimension)
`--sigma`	Double	`1.0`	(optional) the smoothing level
`--amp`	Double	`1.0`	(optional) the
`--threads`	int	`1`	(optional) number of threads
`--preserve`	flag		(optional) pass un-masked values through the filter
`--channel`	Integer		(optional) the volume channel (default applies to all)

Output:

Flag	Type	Description
`--output`	Volume	output filtered volume

VolumeFilterMeanShift

Process a volume with mean shift analysis for either anisotropic filtering or segmentation

Input:

Flag	Type	Description
`--input`	Volume	the input volume
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--hpos`	double	`8.0`	(optional) the spatial bandwidth in mm
`--hval`	double	`64.0`	(optional) the adaptive bandwidth in units of intensity
`--iters`	int	`5000`	(optional) the maxima number of iterations
`--minshift`	double	`0.001`	(optional) the threshold for stopping gradient updates
`--minsize`	double	`50.0`	(optional) the minima cluster size

Output:

Flag	Type	Description
`--filtered`	Volume	(optional) the output filtered image
`--segmented`	Mask	(optional) the output segmentation

Citation: Comaniciu, D., & Meer, P. (2002). Mean shift: A robust approach toward feature space analysis. IEEE Transactions on pattern analysis and machine intelligence, 24(5), 603-619.

VolumeFilterMedian

Filter a volume using a median filter

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mask`	Mask	(optional) input mask

Parameters:

Flag	Type	Default	Description
`--window`	int	`1`	(optional) the window size in voxels
`--channel`	Integer		(optional) the volume channel (default applies to all)
`--slice`	String		(optional) restrict the filtering to a specific slice (i, j, or k)
`--num`	Integer	`1`	(optional) the number of times to filter
`--threads`	Integer	`1`	(optional) the number of threads in the pool

Output:

Flag	Type	Description
`--output`	Volume	output volume

VolumeFilterNLM

Apply a non-local means filter to a volume

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mask`	Mask	(optional) input mask
`--hrelMask`	Mask	(optional) a mask for computing the mean image intensity for relative bandwidth (see hrel)

Parameters:

Flag	Type	Default	Description
`--channel`	Integer		(optional) the volume channel (default applies to all)
`--mode`	FilterMode	`Volumetric`	(optional) indicate whether the filtering should be volumetric (default) or restricted to a specified slice (Options: Volumetric, SliceI, SliceJ, SliceK)
`--patch`	int	`1`	(optional) the patch size
`--search`	int	`2`	(optional) the search window size
`--stats`	int	`2`	(optional) the statistics window size (for computing mean and variance in adaptive filtering)
`--h`	Double		(optional) use a fixed noise level (skips adaptive noise esimation)
`--epsilon`	double	`1.0E-5`	(optional) the minimum meaningful value for mean and vars
`--meanThresh`	double	`0.95`	(optional) the mean intensity threshold
`--varThresh`	double	`0.5`	(optional) the variance intensity threshold
`--factor`	double	`1.0`	(optional) a factor for scaling adaptive sensitivity (larger values remove more noise)
`--hrel`	flag		(optional) use the h bandwidth as a fraction of the mean image intensity
`--hrelwhich`	String	`0`	(optional) specify which channels to use for hrel
`--rician`	flag		(optional) whether a Rician noise model should be used
`--threads`	Integer	`1`	(optional) the number of threads in the pool

Output:

Flag	Type	Description
`--output`	Volume	output volume
`--outputNoise`	Volume	(optional) output noise map

Citation: Manjon, Jose V., et al. Adaptive non-local means denoising of MR images with spatially varying noise levels. Journal of Magnetic Resonance Imaging 31.1 (2010): 192-203.

VolumeFilterNeuron

Filter a volume to isolate neuronal structures

Input:

Flag	Type	Description
`--input`	Volume	input volume

Parameters:

Flag	Type	Default	Description
`--median`	Integer	`1`	(optional) the number of median filter passes
`--dilate`	Integer	`1`	(optional) the number of dilation passes
`--min`	Integer	`300`	(optional) the minimum number of voxels in a neuron connected component
`--thresh`	Double	`0.01`	(optional) the threshold for segmenting cell bodies
`--frangi`	flag		(optional) apply the Frangi filter
`--frangiThresh`	double	`0.01`	(optional) the threshold for Frangi segmentation
`--frangiScales`	int	`5`	(optional) the number of scales used in the Frangi filter
`--frangiLow`	int	`1`	(optional) the lowest scale used in the Frangi filter
`--frangiHigh`	Integer	`10`	(optional) the highest scale used in the Frangi filter
`--threads`	int	`1`	(optional) number of threads

Output:

Flag	Type	Description
`--output`	Volume	output volume
`--outputFrangi`	Volume	(optional) output frangi
`--outputMask`	Mask	(optional) output mask

VolumeFilterPCA

Denoise a volume using random matrix theory. Noise is estimated using a universal Marchenko Pastur distribution and removed via principal component analysis

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mask`	Mask	(optional) input mask

Parameters:

Flag	Type	Default	Description
`--type`	VolumeFilterPCAType	`MP`	(optional) the type of PCA filtering to use (Options: MP, CenterMP)
`--window`	int	`5`	(optional) the window size
`--threads`	Integer	`1`	(optional) the number of threads in the pool

Output:

Flag	Type	Description
`--output`	Volume	output denoised volume
`--noise`	Volume	(optional) output noise map
`--comps`	Volume	(optional) output pca component count

Citation: Veraart, J., Novikov, D. S., Christiaens, D., Ades-Aron, B., Sijbers, J., & Fieremans, E. (2016). Denoising of diffusion MRI using random matrix theory. NeuroImage, 142, 394-406.

VolumeFilterPDE

Filter a volume using a PDE representing anisotropic mri

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mask`	Mask	(optional) input mask

Parameters:

Flag	Type	Default	Description
`--channel`	String		(optional) the volume channel(s) (default applies to all)
`--lambda`	Double	`0.16666666666666666`	(optional) smoothing parameter (in mm)
`--k`	Double	`0.01`	(optional) anisotropic flux parameter (relative to image intensities)
`--steps`	Integer	`5`	(optional) the number of timesteps to apply
`--anisotropic`	flag		(optional) use anisotropic smoothing
`--quadratic`	flag		(optional) use a quadratic flux (instead of exponential)
`--recurse`	flag		(optional) use the output as input

Output:

Flag	Type	Description
`--output`	Volume	output volume

Citation: Perona, P., & Malik, J. (1990). Scale-space and edge detection using anisotropic mri. IEEE Transactions on pattern analysis and machine intelligence, 12(7), 629-639.

VolumeFilterSigmoid

Filter a volume with a sigmoid to perform a soft threshold

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mask`	Mask	(optional) input mask

Parameters:

Flag	Type	Default	Description
`--thresh`	double	`0.5`	(optional) the position of the sigmoid
`--slope`	double	`25.0`	(optional) the slope of the sigmoid
`--low`	double	`0.0`	(optional) low output
`--high`	double	`1.0`	(optional) high output
`--invert`	flag		(optional) invert the sigmoid (lower input values will be high)

Output:

Flag	Type	Description
`--output`	Volume	output mask

VolumeFilterSigmoidRange

Filter a volume with the produce of two sigmoids, which act as a soft range threshold

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mask`	Mask	(optional) input mask

Parameters:

Flag	Type	Default	Description
`--below`	double	`0.5`	(optional) the below sigmoid threshold
`--above`	double	`0.5`	(optional) the above sigmoid threshold
`--slope`	double	`25.0`	(optional) the slope of the sigmoid
`--low`	double	`0.0`	(optional) low output
`--high`	double	`1.0`	(optional) high output
`--invert`	flag		(optional) invert the sigmoid

Output:

Flag	Type	Description
`--output`	Volume	output mask

VolumeFilterTriangle

Filter a volume using a Triangle kernel

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mask`	Mask	(optional) input mask

Parameters:

Flag	Type	Default	Description
`--support`	int	`3`	(optional) filter support (filter will be 2 * support + 1 in each dimension)
`--num`	int	`1`	(optional) number of applications
`--preserve`	flag		(optional) preserve un-masked values through the filter
`--channel`	Integer		(optional) the volume channel (default applies to all)
`--threads`	Integer	`1`	(optional) the number of threads

Output:

Flag	Type	Description
`--output`	Volume	output mask

VolumeFilterZeroCrossing

Filter a volume using a Gaussian kernel

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mask`	Mask	(optional) input mask

Parameters:

Flag	Type	Default	Description
`--large`	flag		(optional) use a bigger 27-voxel neighborhood
`--mode`	Mode	`Both`	(optional) the crossing selection mode (Options: Below, Above, Both)

Output:

Flag	Type	Description
`--output`	Volume	output zero crossings

VolumeFloodFill

Flip the voxel values of volume along coordinate axes

Input:

Flag	Type	Description
`--input`	Volume	input volume of values for filling
`--source`	Mask	a mask indicating the source, i.e. which voxels of the input are used for filling
`--dest`	Mask	(optional) a mask used for restricting the voxel flooded (must be convex, but this is not checked)

Parameters:

Flag	Type	Default	Description
`--fix`	int	`0`	(optional) maximum number of fixing passes

Output:

Flag	Type	Description
`--outputFlood`	Volume	output volume of flood values
`--outputDist`	Volume	(optional) output distance field

VolumeGradient

Compute the gradient of an image

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mask`	Mask	(optional) input mask

Parameters:

Flag	Type	Default	Description
`--channel`	Integer	`0`	(optional) the volume channel (default applies to all)
`--type`	String	`central`	(optional) type of finite difference approximation (forward, backward, central)

Output:

Flag	Type	Description
`--output`	Volume	output volume

VolumeGradientMagnitude

Compute the gradient magnitude of an image

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mask`	Mask	(optional) input mask

Parameters:

Flag	Type	Default	Description
`--channel`	Integer	`0`	(optional) the volume channel (default applies to all)
`--type`	String	`central`	(optional) type of finite difference approximation (forward, backward, central)

Output:

Flag	Type	Description
`--output`	Volume	output volume

VolumeHarmonize

Harmonize a volume with a reference volume

Input:

Flag	Type	Description
`--input`	Volume	the input volume
`--inputMask`	Mask	(optional) an input mask to restrict both statistics and harmonized voxels
`--inputStatMask`	Mask	(optional) an input mask to only restrict computing statistics
`--reference`	Volume	(optional) a reference volume
`--referenceMask`	Mask	(optional) a reference mask

Parameters:

Flag	Type	Default	Description
`--bins`	int	`256`	(optional) the number of bins
`--lower`	Bound	`ThreeStd`	(optional) the method for computing the histogram lower bound (Options: Extrema, Quartile, HalfStd, OneStd, TwoStd, ThreeStd, User)
`--upper`	Bound	`ThreeStd`	(optional) the method for computing the histogram upper bound (Options: Extrema, Quartile, HalfStd, OneStd, TwoStd, ThreeStd, User)
`--mylower`	Double		(optional) specify a specific lower bound for user defined mode
`--myupper`	Double		(optional) specify a specific upper bound for user defined mode
`--smooth`	Double	`10.0`	(optional) the amount of smoothing (relative to bins)
`--lowerThresh`	Double		(optional) a lower threshold for excluding background
`--upperThresh`	Double		(optional) an upper threshold for excluding background

Output:

Flag	Type	Description
`--output`	Volume	the output volume

VolumeHistogram

Compute a histogram of a volume

Input:

Flag	Type	Description
`--input`	Volume	the input volume
`--mask`	Mask	(optional) an input mask

Parameters:

Flag	Type	Default	Description
`--bins`	int	`256`	(optional) the number of bins
`--lower`	Bound	`Extrema`	(optional) the method for computing the histogram lower bound (Options: Extrema, Quartile, HalfStd, OneStd, TwoStd, ThreeStd, User)
`--upper`	Bound	`Extrema`	(optional) the method for computing the histogram upper bound (Options: Extrema, Quartile, HalfStd, OneStd, TwoStd, ThreeStd, User)
`--mylower`	Double		(optional) specify a specific lower bound for user defined mode
`--myupper`	Double		(optional) specify a specific upper bound for user defined mode
`--lowerThresh`	Double		(optional) apply a lower threshold before computing the histogram
`--upperThresh`	Double		(optional) apply an upper threshold before computing the histogram
`--normalize`	flag		(optional) normalize the counts by the total count
`--cdf`	flag		(optional) compute the cdf
`--smooth`	Double		(optional) apply Gaussian smoothing (see hdata)
`--hdata`	flag		(optional) interpret the smoothing parameter relative to the data intensities (default is bins)
`--print`	flag		(optional) print a the histogram to standard output
`--value`	String	`value`	(optional) the value column name

Output:

Flag	Type	Description
`--output`	Table	(optional) an output table

VolumeImpute

Impute voxels by computing a moving average

Input:

Flag	Type	Description
`--input`	Volume	input Volume
`--mask`	Mask	(optional) input mask
`--impute`	Mask	(optional) input imputation mask

Parameters:

Flag	Type	Default	Description
`--support`	int	`5`	(optional) the radius for imputation
`--knn`	int	`6`	(optional) the k-nearest neighbors for imputation
`--missing`	Double		(optional) a value for missing cases (when imputation region is larger than the support)
`--outlier`	Double		(optional) remove extreme values (specify a k value for Tukey’s fence, e.g. 1.5 for outliers or 3 for far out)

Output:

Flag	Type	Description
`--output`	Volume	(optional) output Volume
`--outputOutlier`	Mask	(optional) output outlier mask

VolumeIsotropic

Isotropically scaleCamera a volume

Input:

Flag	Type	Description
`--input`	Volume	the input volume

Parameters:

Flag	Type	Default	Description
`--size`	double	`1.0`	(optional) the output voxel size
`--interp`	InterpolationType	`Tricubic`	(optional) an interpolation type (Options: Nearest, Trilinear, Tricubic, Gaussian, GaussianLocalLinear, GaussianLocalQuadratic)

Output:

Flag	Type	Description
`--output`	Volume	the output volume

VolumeJacobian

Compute the jacobian of a deformation volume

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mask`	Mask	(optional) a mask
`--affine`	Affine	(optional) optional affine component to remove

Parameters:

Flag	Type	Description
`--deformation`	flag	(optional) treat the input as a deformation (i.e. displacement)
`--eigenvalues`	flag	(optional) return the eigenvalues (exclusive with determinant flag)
`--determinant`	flag	(optional) return the determinant (exclusive with eigenvalues flag)
`--logarithm`	flag	(optional) return the logarithm (works with other options)

Output:

Flag	Type	Description
`--output`	Volume	output table

VolumeKurtosisFit

Fit a kurtosis volume. Warning: this does not yet estimate the kurtosis indices, e.g. FA, MK, etc.

Input:

Flag	Type	Description
`--input`	Volume	input diffusion-weighted MR volume
`--gradients`	Gradients	the gradients
`--mask`	Mask	(optional) the mask

Parameters:

Flag	Type	Default	Description
`--method`	KurtosisFitType	`LLS`	(optional) specify an estimation method, (FW enables free water elimination) (Options: LLS, WLLS, FWLLS, FWWLLS)

Advanced Parameters:

Flag	Type	Default	Description
`--shells`	String		(optional) specify a subset of gradient shells to include (comma-separated list of b-values)
`--which`	String		(optional) specify a subset of gradients to include (comma-separated list of indices starting from zero)
`--exclude`	String		(optional) specify a subset of gradients to exclude (comma-separated list of indices starting from zero)
`--threads`	int	`1`	(optional) the number of threads to use

Output:

Flag	Type	Description
`--output`	Volume	output kurtosis volume

Citation: Veraart, J., Sijbers, J., Sunaert, S., Leemans, A., Jeurissen, B.: Weighted linear least squares estimation of mri mri parameters: strengths, limitations, and pitfalls. NeuroImage 81 (2013) 335-346

VolumeKurtosisODF

Sample an orientation distribution function (ODF) from a kurtosis volume.

Input:

Flag	Type	Description
`--input`	Volume	the input kurtosis volume
`--dirs`	Vects	the sphere directions
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--alpha`	Double	`10.0`	(optional) the alpha power value
`--detail`	Integer	`4`	(optional) the level of detail for spherical ODF sampling
`--threads`	Integer	`1`	(optional) the number of threads in the pool

Output:

Flag	Type	Description
`--output`	Volume	the output odf volume

VolumeKurtosisPeaks

Extract the peaks from a kurtosis volume. This finds the average direction of local maxima clustered by hierarchical clustering. The output fibers will encode the peak ODF value in place of volume fraction.

Input:

Flag	Type	Description
`--input`	Volume	the input kurtosis volume
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--comps`	Integer	`3`	(optional) the maximum number of comps
`--alpha`	Double	`10.0`	(optional) the alpha power value
`--thresh`	Double	`0.0`	(optional) the minimum peak threshold
`--detail`	Integer	`4`	(optional) the level of detail for spherical ODF sampling
`--cluster`	Double	`5.0`	(optional) the minimum angle in degrees for hierarchical clustering of local maxima
`--threads`	Integer	`1`	(optional) the number of threads in the pool

Output:

Flag	Type	Description
`--output`	Volume	the output fibers volume

VolumeMagnitude

Compute the magnitude of an image

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mask`	Mask	(optional) input mask

Output:

Flag	Type	Description
`--output`	Volume	output volume

VolumeMarchingCubes

Extract a mesh from a volume level set. This can be used for extracting boundary surfaces of distance fields, probability maps, parametric maps, etc. The background level should be changed depending on the context though to make sure the mesh orientation is correct.

Input:

Flag	Type	Description
`--input`	Volume	input volume

Parameters:

Flag	Type	Default	Description
`--level`	double	`0.5`	(optional) level set to extract
`--background`	double	`0.0`	(optional) background value for outside sampling range (should be zero if the background is ‘black’ and a large number if the input is similar to a distance field)
`--nobound`	flag		(optional) exclude triangles on the boundary of the volume
`--largest`	flag		(optional) retain only the largest component
`--multi`	flag		(optional) extract a mesh for every channel
`--label`	String	`label`	(optional) a label attribute name for multi-channel extraction
`--median`	Integer		(optional) apply a median filter a given number of times before surface extraction
`--std`	Double		(optional) apply g Gaussian smoothing before surface extraction
`--support`	Integer	`3`	(optional) use a given support in voxels for voxel smoothing
`--meanarea`	Double		(optional) simplify the mesh to have the given mean triangle area
`--noboundmesh`	flag		(optional) do not simplify vertices on the mesh boundary
`--smooth`	Double		(optional) smooth the mesh

Output:

Flag	Type	Description
`--output`	Mesh	output mesh

Citation: Lorensen, W. E., & Cline, H. E. (1987, August). Marching cubes: A high resolution 3D surface construction algorithm. In ACM SIGGRAPH Computer Graphics (Vol. 21, No. 4, pp. 163-169)

VolumeMarchingSquares

Extract isocontours from slices of a volume

Input:

Flag	Type	Description
`--input`	Volume	input volume

Parameters:

Flag	Type	Default	Description
`--level`	double	`0.0`	(optional) level set to extract
`--background`	double	`1.7976931348623157E308`	(optional) background value for outside sampling range
`--dim`	String	`z`	(optional) volume channel to contour (x, y, or z)
`--start`	int	`0`	(optional) starting slice index
`--step`	int	`1`	(optional) number of slices between contours

Output:

Flag	Type	Description
`--output`	Curves	output contours

Citation: Maple, C. (2003, July). Geometric design and space planning using the marching squares and marching cube algorithms. In Geometric Modeling and Graphics, 2003. Proceedings. 2003 International Conference on (pp. 90-95). IEEE.

VolumeMask

Mask a volume

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mask`	Mask	a mask

Output:

Flag	Type	Description
`--output`	Volume	output volume

VolumeMaxProb

Find the maxima probability labels

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mask`	Mask	(optional) a mask to indicate background

Parameters:

Flag	Type	Default	Description
`--bglabel`	int	`0`	(optional) the background label
`--bgvalue`	double	`1.0`	(optional) the background value

Output:

Flag	Type	Description
`--labels`	Mask	(optional) output mask of the extremal index
`--values`	Volume	(optional) output volume of the extremal values

VolumeMcsmtFit

Estimate multi-compartment microscopic diffusion parameters

Input:

Flag	Type	Description
`--input`	Volume	the input diffusion-weighted MR volume
`--gradients`	Gradients	the input gradients
`--mask`	Mask	(optional) the input mask

Parameters:

Flag	Type	Default	Description
`--threads`	int	`1`	(optional) the input number of threads

Advanced Parameters:

Flag	Type	Default	Description
`--maxiters`	int	`1500`	(optional) the maximum number of iterations
`--rhobeg`	double	`0.1`	(optional) the starting simplex size
`--rhoend`	double	`0.001`	(optional) the ending simplex size
`--dint`	double	`0.0017`	(optional) the initial guess for parallel diffusivity
`--frac`	double	`0.5`	(optional) the initial guess for intra-neurite volume fraction
`--fscale`	double	`10.0`	(optional) the scaling for volume fraction optimization
`--dscale`	double	`1000.0`	(optional) the scaling for diffusivity optimization
`--dmax`	double	`0.003`	(optional) the maximum diffusivity
`--dot`	flag		(optional) include a dot compartment

Output:

Flag	Type	Description
`--output`	Volume	the output parameter map

Citation: Kaden, E., Kelm, N. D., Carson, R. P., Does, M. D., & Alexander, D. C. (2016). Multi-compartment microscopic diffusion imaging. NeuroImage, 139, 346-359.

VolumeMcsmtTransform

Transform an mcsmt volume

Input:

Flag	Type	Description
`--input`	Volume	the input mcsmt volume
`--reference`	Volume	input reference volume
`--mask`	Mask	(optional) input mask
`--inputMask`	Mask	(optional) use an input mask (defined in the input space)
`--affine`	Affine	(optional) apply an affine xfm
`--invaffine`	Affine	(optional) apply an inverse affine xfm
`--deform`	Deformation	(optional) apply a deformation xfm

Parameters:

Flag	Type	Default	Description
`--reverse`	flag		(optional) reverse the order, i.e. compose the affine(deform(x)), whereas the default is deform(affine(x))
`--reorient`	ReorientationType	`Jacobian`	(optional) specify a reorient method (Options: FiniteStrain, Jacobian)
`--interp`	KernelInterpolationType	`Trilinear`	(optional) the interpolation type (Options: Nearest, Trilinear, Gaussian)
`--support`	Integer	`3`	(optional) the filter radius in voxels
`--hpos`	Double	`1.0`	(optional) the positional bandwidth in mm

Output:

Flag	Type	Description
`--output`	Volume	the output transformed mcsmt volume

VolumeMeasure

Collect statistical sumaries of a volume using a mask. This supports single label masks and more advanced options for multi-channel masks (e.g. loading names associated with each label)

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--weight`	Volume	(optional) a weighting
`--mask`	Mask	(optional) a mask
`--lookup`	Table	(optional) use a lookup for region names

Parameters:

Flag	Type	Default	Description
`--background`	flag		(optional) use the background
`--multiple`	flag		(optional) use multiple regions
`--channel`	int	`0`	(optional) specify a volume channel
`--base`	String	`region`	(optional) specify a region basename
`--index`	String	`index`	(optional) specify the lookup index field
`--name`	String	`name`	(optional) specify the lookup name field
`--region`	String	`region`	(optional) specify the output region field name
`--stat`	String	`stat`	(optional) specify the output statistic field name
`--value`	String	`value`	(optional) specify the output value field name
`--include`	String		(optional) specify which statistics should be included (e.g. mean)
`--union`	flag		(optional) combine the region and stat fields into one
`--join`	String	`_`	(optional) the character for joining region and stat names (depends on union flag)
`--nostat`	flag		(optional) exclude the statistics field
`--widen`	flag		(optional) widen the table on the statistics field

Output:

Flag	Type	Description
`--output`	Table	output table

VolumeMeasureMulti

Collect statistical sumaries of a volume using a mask. This supports single label masks and more advanced options for multi-label masks (e.g. loading names associated with each label)

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--weight`	Volume	(optional) a weighting
`--mask`	Mask	(optional) a mask
`--lookup`	Table	(optional) use a lookup for region names

Parameters:

Flag	Type	Default	Description
`--background`	flag		(optional) use the background
`--multiple`	flag		(optional) use multiple regions
`--base`	String	`region`	(optional) specify a region basename
`--index`	String	`index`	(optional) specify the lookup index field
`--channel`	String	`channel`	(optional) specify the channel index field
`--name`	String	`name`	(optional) specify the lookup name field
`--region`	String	`region`	(optional) specify the output region field name
`--stat`	String	`stat`	(optional) specify the output statistic field name
`--value`	String	`value`	(optional) specify the output value field name
`--include`	String		(optional) specify which statistics should be included (e.g. mean)
`--union`	flag		(optional) combine the region and stat fields into one
`--join`	String	`_`	(optional) the character for joining region and stat names (depends on union flag)
`--nostat`	flag		(optional) exclude the statistics field
`--widen`	flag		(optional) widen the table on the statistics field

Output:

Flag	Type	Description
`--output`	Table	output table

VolumeModelError

Compute the root mean square error between a model and dwi volume

Input:

Flag	Type	Description
`--input`	Volume	input model volume
`--dwi`	Volume	input dwi
`--gradients`	Gradients	input gradients
`--mask`	Mask	(optional) input mask

Parameters:

Flag	Type	Default	Description
`--model`	String		(optional) a model name (default will try to detect it)
`--type`	ModelErrorType	`RMSE`	(optional) specify an error type (default is root mean square error) (Options: MAD, NMAD, MSE, RMSE, NRMSE, BIC, AIC, AICc)
`--dof`	Integer		(optional) specify an specific degrees of freedom (useful for models that were constrained when fitting)
`--dparNoddi`	Double		(optional) specify a NODDI parallel diffusivity
`--disoNoddi`	Double		(optional) specify a NODDI isotropic diffusivity

Output:

Flag	Type	Description
`--output`	Volume	output error volume

Citation: Burnham, K. P., & Anderson, D. R. (2004). Multimodel inference: understanding AIC and BIC in model selection. Sociological methods & research, 33(2), 261-304.

VolumeModelFeature

Extract a feature from a model volume

Input:

Flag	Type	Description
`--input`	Volume	input model volume

Parameters:

Flag	Type	Default	Description
`--model`	String		(optional) a model name (default will try to detect it)
`--feature`	String		(optional) a feature name

Output:

Flag	Type	Description
`--output`	Volume	output feature volume

VolumeModelReorient

Reorient the fiber orientations of a model volume. If both a flip and swap are specified, the flip is performed first. This only works for tensor, noddi, and fibers volumes

Input:

Flag	Type	Description
`--input`	Volume	input model volume
`--mask`	Mask	(optional) input mask

Parameters:

Flag	Type	Description
`--model`	String	(optional) a model name (default will try to detect it)
`--flip`	String	(optional) flip a coodinate (x, y, z, or none)
`--swap`	String	(optional) swap a pair of coordinates (xy, xz, yz, or none)

Output:

Flag	Type	Description
`--output`	Volume	output error volume

VolumeModelSample

Sample model parameters based on a variety of possible data objects

Input:

Flag	Type	Description
`--input`	Volume	the input model volume
`--vects`	Vects	(optional) vects storing the position where models should be sampled
`--solids`	Solids	(optional) solids storing the position where models should be sampled
`--mask`	Mask	(optional) mask storing the position where models should be sampled
`--curves`	Curves	(optional) curves storing the position where models should be sampled
`--mesh`	Mesh	(optional) mesh storing the position where models should be sampled

Parameters:

Flag	Type	Default	Description
`--model`	ModelType	`Vect`	(optional) a model type (if you select None, the code will try to detect it) (Options: Vect, Tensor, BiTensor, Fibers, Spharm, Kurtosis, Noddi, ExpDecay, Mcsmt)
`--jitter`	Double		(optional) jitter the samples by a given amount
`--cull`	Double		(optional) cull the samples at a given threshold ditance
`--multiplier`	Integer	`1`	(optional) a multiplier of the number of samples taken (sometimes only makes sense when jittering)
`--limit`	Integer		(optional) a maximum number of samples (the excess is randomly selected)
`--param`	flag		(optional) samples should store only model parameters (otherwise the position is prepended)

Advanced Parameters:

Flag	Type	Default	Description
`--interp`	KernelInterpolationType	`Trilinear`	(optional) the interpolation type (Options: Nearest, Trilinear, Gaussian)
`--support`	Integer	`5`	(optional) the interpolation filter radius in voxels
`--hpos`	Double	`1.5`	(optional) the positional interpolation bandwidth in mm
`--comps`	int	`3`	(optional) a maxima number of compartments (xfib only)
`--log`	flag		(optional) use log-euclidean estimation (dti only)
`--threads`	int	`4`	(optional) the number of threads

Output:

Flag	Type	Description
`--output`	Vects	the output sampled vects

Citation: Cabeen, R. P., Bastin, M. E., & Laidlaw, D. H. (2016). Kernel regression estimation of fiber orientation mixtures in mri MRI. NeuroImage, 127, 158-172.

VolumeModelSynth

Synthesize a dMRI from a fibers volume

Input:

Flag	Type	Description
`--input`	Volume	input model volume
`--gradients`	Gradients	the gradient scheme
`--mask`	Mask	(optional) input mask

Parameters:

Flag	Type	Default	Description
`--model`	String		(optional) a model name (default will try to detect it)

Output:

Flag	Type	Description
`--output`	Volume	output synthesized diffusion-weighted MR volume

VolumeModelTrackStreamline

Perform deterministic multi-fiber streamline tractography from a model volume. This supports tensor, fibers, spharm, and noddi volumes.

Input:

Flag	Type	Description
`--input`	Volume	the input model volume
`--seedVects`	Vects	(optional) seed from vects
`--seedMask`	Mask	(optional) a seed mask (one seed per voxel is initiated from this)
`--seedSolids`	Solids	(optional) seed from solids (one seed per object is initiated from this)
`--includeMask`	Mask	(optional) an include mask (curves are only included if they touch this, i.e. AND)
`--includeSolids`	Solids	(optional) an include solids (curves are only included if they touch this, i.e. AND)
`--includeAddMask`	Mask	(optional) an additional include mask (curves are only included if they touch this, i.e. AND)
`--includeAddSolids`	Solids	(optional) an additional include solids (curves are only included if they touch this, i.e. AND)
`--excludeMask`	Mask	(optional) an exclude mask (curves are removed if they touch this mask, i.e. NOT)
`--excludeSolids`	Solids	(optional) an exclude solids object (curves are removed if they touch any solid, ie.e NOT)
`--trapMask`	Mask	(optional) a trap mask (tracking terminates when leaving this mask)
`--stopMask`	Mask	(optional) a stop mask (tracking terminates when reaching this mask)
`--stopSolids`	Solids	(optional) a stop solids object (tracking terminates when reaching any solid)
`--endMask`	Mask	(optional) an endpoint mask (curves are only retained if they end inside this)
`--endSolids`	Solids	(optional) an endpoint solids object (curves are only retained if they end inside this)
`--trackMask`	Mask	(optional) a tracking mask (tracking is stopped if a curve exits this mask)
`--trackSolids`	Solids	(optional) a tracking solids (tracking is stopped if a curve exits solids)
`--containMask`	Mask	(optional) a containment mask (a minimum fraction of arclength must be inside this mask)
`--connectMask`	Mask	(optional) a connection mask (tracks will be constrained to connect distinct labels)
`--odfPoints`	Vects	(optional) specify the spherical points for processing the odf (the number of vectors should match the dimensionality of the input volume)
`--force`	Volume	(optional) use a force field
`--hybridPeaks`	Volume	(optional) use the given peaks (otherwise they will be computed from the input)
`--hybridConnectMask`	Mask	(optional) use the given connect mask during the initial tracking phase (but not the secondary one)
`--hybridTrapMask`	Mask	(optional) use the given trap mask during the initial tracking phase (but not the secondary one)
`--hybridExcludeMask`	Mask	(optional) use the given exclude mask during the initial tracking phase (but not the secondary one)
`--hybridStopMask`	Mask	(optional) use the given stop mask during the initial tracking phase (but not the secondary one)
`--hybridTrackMask`	Mask	(optional) use the given track mask during the initial tracking phase (but not the secondary one)
`--hybridCurves`	Curves	(optional) use the given curves (and skip the first stage of hybrid tracking)

Parameters:

Flag	Type	Default	Description
`--samplesFactor`	Double	`1.0`	(optional) increase or decrease the total number of samples by a given factor (regardless of whether using vects, mask, or solids)
`--samplesMask`	Integer	`1`	(optional) the number of samples per voxel when using mask seeding
`--samplesSolids`	Integer	`5000`	(optional) the number of samples per object when using solid seeding
`--min`	double	`0.075`	(optional) a minimum cutoff value for tracking (depend on the voxel model, e.g. FA for DTI, frac for Fibers, etc.)
`--angle`	Double	`45.0`	(optional) the angle stopping criteria (maximum change in orientation per step)
`--disperse`	Double	`0.0`	(optional) use a fixed amount of orientation dispersion during tracking (e.g. 0.1)
`--step`	Double	`1.0`	(optional) the step size for tracking
`--minlen`	Double	`0.0`	(optional) the minimum streamline length
`--maxlen`	Double	`1000000.0`	(optional) the maximum streamline length
`--maxseeds`	Integer	`2000000`	(optional) a maximum number of seeds
`--maxtracks`	Integer	`2000000`	(optional) a maximum number of tracks
`--interp`	KernelInterpolationType	`Nearest`	(optional) the interpolation type (Options: Nearest, Trilinear, Gaussian)
`--mono`	flag		(optional) use monodirectional seeding (default is bidirectional), e.g. for seeding from a subcortical structure
`--prob`	flag		(optional) use probabilistic sampling and selection
`--probMax`	flag		(optional) follow the maximum probability direction (only used when the prob flag is enabled)
`--probPower`	Double	`1.0`	(optional) raise the sample probability to the given power (to disable, leave at one)
`--probAngle`	Double	`5.0`	(optional) the prior gain for angle changes (beta * change / threshold) (t disable, set to zero)
`--probPoints`	Integer	`300`	(optional) the number of ODF points to sample for probabilistic sampling (or you can provide specific odfPoints)
`--endConnect`	flag		(optional) find connections in the end mask
`--quiet`	flag		(optional) print progress messages

Advanced Parameters:

Flag	Type	Default	Description
`--vector`	flag		(optional) use vector field integration (the default is to use axes, which have not preferred forward/back direction)
`--hybrid`	flag		(optional) use the hybrid approach
`--hybridSamplesFactor`	Double	`1.0`	(optional) specify a seed multiplication factor for the first stage of hybrid tracking
`--hybridMin`	Double		(optional) specify an minimum for the first stage of hybrid tracking
`--hybridAngle`	Double		(optional) specify an angle for the first stage of hybrid tracking
`--hybridDisperse`	Double	`0.1`	(optional) specify an amount of dispersion to in the first stage of hybrid tracking
`--hybridPresmooth`	Double		(optional) specify an pre-smoothing bandwidth (before projection)
`--hybridProjAngle`	Double	`45.0`	(optional) specify an angle for hybrid projection
`--hybridProjNorm`	Double	`0.01`	(optional) specify a minimum norm for hybrid projection
`--hybridProjFrac`	Double	`0.025`	(optional) specify a minimum compartment fraction for hybrid projection
`--hybridProjFsum`	Double	`0.05`	(optional) specify a minimum total fraction for hybrid projection
`--hybridPostsmooth`	Double		(optional) specify an post-smoothing bandwidth (after projection)
`--hybridInterp`	KernelInterpolationType	`Nearest`	(optional) the interpolation type for the first stage of hybrid tracking (Options: Nearest, Trilinear, Gaussian)
`--gforce`	Double	`0.0`	(optional) the prior gain forces (larger values have smoother effects and zero is hard selection)
`--model`	String		(optional) a model name (default will try to detect it)
`--threads`	int	`3`	(optional) the number of threads
`--max`	Double		(optional) a maximum value for tracking (FA for dti, frac for xfib/spharm, ficvf for noddi)
`--mixing`	Double	`1.0`	(optional) the mixing weight for orientation updates (0 to 1)
`--arclen`	Double	`0.8`	(optional) an arclength containment threshold
`--reach`	Double		(optional) only allow tracking to travel a given reach distance from the seed
`--rk`	flag		(optional) use fourth-order Runge-Kutta integration (default is Euler)
`--binarize`	flag		(optional) binarize masks (ignore multiple labels in include and other masks)

Output:

Flag	Type	Description
`--output`	Curves	the output tractography curves

Citation: Cabeen, R. P., Bastin, M. E., & Laidlaw, D. H. (2016). Kernel regression estimation of fiber orientation mixtures in diffusion MRI. NeuroImage, 127, 158-172.

VolumeMosaic

Create a mosaic from an image volume. This will take a 3D volume and create a single slice that shows the whole dataset. This is mainly useful for quality assessment.

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mask`	Mask	(optional) input mask

Parameters:

Flag	Type	Default	Description
`--output`	String		output filename to save mosaic
`--axis`	VolumeMosaicAxis	`i`	(optional) choose an axis for slicing (Options: i, j, k)
`--crop`	String		(optional) a string for cropping the volume, e.g. :,:,10:2:17 would show slices 10, 12, 14, and 16 etc.
`--rgb`	flag		(optional) treat the input as RGB
`--enhance`	flag		(optional) enhance the contrast
`--min`	Double		(optional) use a linear colormap with the given fixed minimum
`--max`	Double		(optional) use a linear colormap with the given fixed maximum
`--multichannel`	flag		(optional) save out multichannel slices (the output filename must include ‘%d’ if you use this option)

VolumeNiftiCopyHeader

Copy the image data of the input image into a reference volume’s nifti header

Parameters:

Flag	Type	Description
`--input`	String	the filename of the input volume (the source of data)
`--ref`	String	the filename of input reference volume (for providing the header)
`--output`	String	the filename of the output volume

VolumeNiftiPrintHeader

Print the header of the given nifti file (this is faster than other modules because it doesn’t read the image data)

Parameters:

Flag	Type	Default	Description
`--input`	String		the filename of the input volume
`--table`	flag		(optional) write the summary as a table

VolumeNiftiRead

Load a nifti in a non-standard way, e.g. setting certain header fields before loading the image data

Parameters:

Flag	Type	Description
`--input`	String	the filename of the input nifti volume
`--scl_slope`	Double	(optional) set the scl_slope field to a certain value
`--scl_inter`	Double	(optional) set the scl_inter field to a certain value

Output:

Flag	Type	Description
`--output`	Volume	the filename of the output volume

VolumeNiftiVoxelToWorld

Extract the affine transform between voxel and world coordinates (note: this is designed for nifti volumes that have some arbitrary voxel ordering)

Input:

Flag	Type	Description
`--input`	Volume	input Volume

Parameters:

Flag	Type	Description
`--noscale`	flag	(optional) skip the scaling
`--notrans`	flag	(optional) skip the translation
`--norot`	flag	(optional) skip the rotation

Output:

Flag	Type	Description
`--output`	Affine	output affine

VolumeNoddiAbtin

Extract ABTIN (ABsolute TIssue density from NODDI) parameters from a noddi volume. Port from: https://github.com/sepehrband/ABTIN/blob/master/ABTIN.m

Input:

Flag	Type	Description
`--input`	Volume	input noddi volume
`--mask`	Mask	(optional) the mask

Parameters:

Flag	Type	Default	Description
`--alpha`	double	`25.0`	(optional) the alpha parameter (see theory section of paper)
`--gratio`	double	`0.7`	(optional) the alpha parameter (see theory section of paper)

Output:

Flag	Type	Description
`--outputMylDen`	Volume	output myelin density volume
`--outputCSFDen`	Volume	output CSF density volume
`--outputFibDen`	Volume	output fiber density volume
`--outputCelDen`	Volume	output cellular density volume

Citation: Sepehrband, F., Clark, K. A., Ullmann, J. F.P., Kurniawan, N. D., Leanage, G., Reutens, D. C. and Yang, Z. (2015), Brain tissue compartment density estimated using diffusion-weighted MRI yields tissue parameters consistent with histology. Hum. Brain Mapp.. doi: 10.1002/hbm.22872 Link: http://onlinelibrary.wiley.com/doi/10.1002/hbm.22872/abstract

VolumeNoddiCortex

Estimate cortical gray matter noddi parameters

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mesh`	Mesh	input mesh
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--interp`	KernelInterpolationType	`Trilinear`	(optional) the interpolation type (Options: Nearest, Trilinear, Gaussian)
`--estimation`	String	`Component`	(optional) specify an estimation method
`--support`	Integer	`3`	(optional) the filter radius in voxels
`--hpos`	Double	`1.0`	(optional) the positional bandwidth in mm
`--pial`	String	`pial`	(optional) pial attribute name
`--white`	String	`white`	(optional) white attribute name
`--samples`	int	`15`	(optional) the number of points to sample
`--inner`	double	`0.5`	(optional) the inner search buffer size
`--outer`	double	`0.5`	(optional) the outer search buffer size
`--maxiso`	Double	`0.5`	(optional) the maximum isotropic volume fraction
`--zscore`	Double	`3.0`	(optional) the maximum isotropic volume fraction

Output:

Flag	Type	Description
`--output`	Mesh	the output mesh
`--weights`	Volume	(optional) the output weights

VolumeNoddiFit

Fit a noddi volume

Input:

Flag	Type	Description
`--input`	Volume	input diffusion-weighted MR volume
`--gradients`	Gradients	the gradients
`--mask`	Mask	(optional) the mask

Parameters:

Flag	Type	Default	Description
`--method`	VolumeNoddiFitMethod	`FullSMT`	(optional) the method for fitting (Options: SmartStart, FullSMT, SMT, FastSMT, NLLS, Grid)
`--dpar`	Double	`0.0017`	(optional) the parallel diffusivity (change for ex vivo)
`--diso`	Double	`0.003`	(optional) the isotropic diffusivity (change for ex vivo)
`--dot`	flag		(optional) include a dot compartment (set for ex vivo)
`--threads`	Integer	`1`	(optional) the number of threads in the pool
`--columns`	flag		(optional) use fine-grained multi-threading

Advanced Parameters:

Flag	Type	Default	Description
`--shells`	String		(optional) specify a subset of gradient shells to include (comma-separated list of b-values)
`--which`	String		(optional) specify a subset of gradients to include (comma-separated list of indices starting from zero)
`--exclude`	String		(optional) specify a subset of gradients to exclude (comma-separated list of indices starting from zero)
`--maxiter`	Integer	`100`	(optional) specify a maximum number of iterations for non-linear optimization
`--rhobeg`	double	`0.1`	(optional) specify the starting rho parameter for non-linear optimization
`--rhoend`	double	`1.0E-4`	(optional) specify the ending rho parameter for non-linear optimization
`--prior`	Double		(optional) specify the prior for regularizing voxels with mostly free water, a value between zero and one that indicates substantial free water, e.g. 0.95)

Output:

Flag	Type	Description
`--output`	Volume	output noddi volume (name output like *.noddi and an directory of volumes will be created)

VolumeNoddiSmooth

Smooth a noddi volume

Input:

Flag	Type	Description
`--input`	Volume	the input Noddi volume
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--support`	Integer	`3`	(optional) the filter radius in voxels
`--hpos`	Double	`1.0`	(optional) the positional bandwidth in mm
`--hdir`	Double		(optional) the directionally adaptive bandwidth (only used with adaptive flag)
`--hsig`	Double		(optional) the baseline signal adaptive bandwidth
`--estimation`	String	`Scatter`	(optional) specify an estimation method

Output:

Flag	Type	Description
`--output`	Volume	the output noddi volume

VolumeNoddiTransform

Transform a noddi volume

Input:

Flag	Type	Description
`--input`	Volume	the input noddi volume
`--reference`	Volume	input reference volume
`--mask`	Mask	(optional) input mask (defined in the reference space)
`--inputMask`	Mask	(optional) use an input mask (defined in the input space)
`--affine`	Affine	(optional) apply an affine xfm
`--invaffine`	Affine	(optional) apply an inverse affine xfm
`--deform`	Deformation	(optional) apply a deformation xfm

Parameters:

Flag	Type	Default	Description
`--reverse`	flag		(optional) reverse the order, i.e. compose the affine(deform(x)), whereas the default is deform(affine(x))
`--reorient`	ReorientationType	`Jacobian`	(optional) specify a reorient method (Options: FiniteStrain, Jacobian)
`--interp`	KernelInterpolationType	`Trilinear`	(optional) the interpolation type (Options: Nearest, Trilinear, Gaussian)
`--support`	Integer	`3`	(optional) the filter radius in voxels
`--hpos`	Double	`1.0`	(optional) the positional bandwidth in mm
`--estimation`	String	`Component`	(optional) specify an estimation method

Output:

Flag	Type	Description
`--output`	Volume	the output transformed noddi volume

VolumeNoddiZoom

Zoom a noddi volume

Input:

Flag	Type	Description
`--input`	Volume	the input noddi volume
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--factor`	double	`2.0`	(optional) a zooming factor
`--interp`	KernelInterpolationType	`Trilinear`	(optional) the interpolation type (Options: Nearest, Trilinear, Gaussian)
`--support`	Integer	`3`	(optional) the filter radius in voxels
`--hpos`	Double	`2.0`	(optional) the positional kernel bandwidth in mm
`--hval`	Double		(optional) the data kernel bandwidth
`--hsig`	Double		(optional) the signal kernel bandwidth
`--estimation`	String	`Scatter`	(optional) specify an estimation method

Output:

Flag	Type	Description
`--output`	Volume	the output noddi volume

VolumeNoise

Add synthetic noise to a volume

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mask`	Mask	(optional) input mask

Parameters:

Flag	Type	Default	Description
`--sigma`	double	`1.0`	(optional) noise level
`--rician`	flag		(optional) use rician distributed noise

Output:

Flag	Type	Description
`--output`	Volume	output mask

VolumeNormalize

Normalize the values of a volume

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mask`	Mask	(optional) input mask

Parameters:

Flag	Type	Default	Description
`--type`	VolumeNormalizeType	`UnitMax`	(optional) type of normalization (Options: Unit, UnitMax, UnitSum, UnitMean, Mean, UnitMaxFraction, UnitMeanFraction, Gaussian)
`--fraction`	double	`0.5`	(optional) a fraction for normalization (only applies to some types of normalization)

Output:

Flag	Type	Description
`--output`	Volume	output volume

VolumeOdfFeature

Estimate spherical harmonics representing the ODF. SUpported features include: generalized fractional anisotropy (GFA) and normalized entropy (NE)

Input:

Flag	Type	Description
`--input`	Volume	the input ODF volume
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--name`	String	`GFA`	(optional) the name of the feature (GFA, NE)
`--threads`	Integer	`1`	(optional) the number of threads in the pool

Output:

Flag	Type	Description
`--output`	Volume	the output spharm volume

VolumeOdfFit

Fit an orientation distribution function (ODF) using spherical deconvolution

Input:

Flag	Type	Description
`--input`	Volume	the input dwi
`--gradients`	Gradients	the gradients
`--points`	Vects	(optional) the input odf directions (if you don’t provide this, you they will be generated and returned in outpoints)
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--num`	int	`300`	(optional) the number of points to use if you need to generate spherical points
`--iters`	int	`500`	(optional) the number of iterations for deconvolution
`--alpha`	double	`0.0017`	(optional) the kernel diffusivity for deconvolution
`--beta`	double	`0.0`	(optional) the kernel radial diffusivity for deconvolution
`--threads`	Integer	`1`	(optional) the number of threads in the pool

Advanced Parameters:

Flag	Type	Description
`--shells`	String	(optional) specify a subset of gradient shells to include (comma-separated list of b-values)
`--which`	String	(optional) specify a subset of gradients to include (comma-separated list of indices starting from zero)
`--exclude`	String	(optional) specify a subset of gradients to exclude (comma-separated list of indices starting from zero)

Output:

Flag	Type	Description
`--output`	Volume	the output ODF volume
`--outpoints`	Vects	(optional) the output odf directions (only relevant if you didn’t provide a specific set)

Citation: Dell’Acqua, F., Scifo, P., Rizzo, G., Catani, M., Simmons, A., Scotti, G., & Fazio, F. (2010). A modified damped Richardson-Lucy algorithm to reduce isotropic background effects in spherical deconvolution. Neuroimage, 49(2), 1446-1458.

VolumeOdfPeaks

Extract the peaks from an odf volume. This finds the average direction of local maxima clustered by hierarchical clustering. The output fibers will encode the peak ODF value in place of volume fraction.

Input:

Flag	Type	Description
`--input`	Volume	the input ODF volume
`--points`	Vects	the odf directions
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--comps`	Integer	`3`	(optional) the maximum number of comps
`--gfa`	flag		(optional) scaleCamera peak values by generalized fractional anisotropy after extraction
`--thresh`	Double	`0.01`	(optional) the minimum peak threshold
`--mode`	PeakMode	`Mean`	(optional) the mode for extracting the peak fraction from the lobe (Options: Sum, Mean, Max)
`--cluster`	Double	`25.0`	(optional) the minimum angle in degrees for hierarchical clustering of local maxima
`--match`	flag		(optional) match the ODF sum
`--threads`	Integer	`1`	(optional) the number of threads in the pool

Output:

Flag	Type	Description
`--output`	Volume	the output fibers volume

VolumeOdfResample

Resample an ODF using spherical harmonics. Using a lower maximum order will lead to smoother resamplings

Input:

Flag	Type	Description
`--input`	Volume	the input ODF volume
`--dirs`	Vects	the input odf directions
`--resample`	Vects	the directions to resample
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--order`	Integer	`8`	(optional) the maximum spherical harmonic order used for resampling
`--threads`	Integer	`1`	(optional) the number of threads in the pool

Output:

Flag	Type	Description
`--output`	Volume	the output ODF volume

VolumeOdfSpharm

Estimate spherical harmonics representing the ODF

Input:

Flag	Type	Description
`--input`	Volume	the input ODF volume
`--dirs`	Vects	the odf directions
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--order`	Integer	`8`	(optional) the maximum spherical harmonic order
`--threads`	Integer	`1`	(optional) the number of threads in the pool

Output:

Flag	Type	Description
`--output`	Volume	the output spharm volume

VolumeOrigin

set the origin of a volume

Input:

Flag	Type	Description
`--input`	Volume	the input volume

Parameters:

Flag	Type	Default	Description
`--x`	double	`0.0`	(optional) the origin in x
`--y`	double	`0.0`	(optional) the origin in y
`--z`	double	`0.0`	(optional) the origin in z

Output:

Flag	Type	Description
`--output`	Volume	the output volume

VolumePad

Pad a volume by a given number of voxels

Input:

Flag	Type	Description
`--input`	Volume	input mask

Parameters:

Flag	Type	Default	Description
`--pad`	int	`10`	(optional) the amount of padding in voxels

Output:

Flag	Type	Description
`--output`	Volume	output mask

VolumeParticles

Create particles representing a volume

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mask`	Mask	(optional) input mask

Parameters:

Flag	Type	Default	Description
`--output`	String		output filename (should end in csv)
`--samples`	int	`4`	(optional) at most, produce this many samples per voxel
`--adaptive`	flag		(optional) sample particles adaptively, that is, most particles with higher image intensities
`--thresh`	double	`0.0`	(optional) specify a threshold for background removal, e.g. 0.01 (based on input image intensities)
`--type`	VolumeEnhanceContrastType	`Ramp`	(optional) use the given type of contrast enhancement to normalize the image (Options: Histogram, Ramp, RampGauss, Mean, None)
`--interp`	InterpolationType	`Nearest`	(optional) use the given image interpolation method (Options: Nearest, Trilinear, Tricubic, Gaussian, GaussianLocalLinear, GaussianLocalQuadratic)

VolumePerturbDeform

Perturb a volume morphometry for data augmentation

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--deform`	Mask	(optional) apply a deform in the given region

Parameters:

Flag	Type	Default	Description
`--flip`	Double		(optional) specify the probability of a flip perturbation (zero to one)
`--angle`	Double		(optional) specify the sampling standard deviation of the angular perturbation (degrees)
`--scale`	Double		(optional) specify the sampling standard deviation of the total scaling perturbation (added to a scaling factor of one)
`--aniso`	Double		(optional) specify the sampling standard deviation of the anisotropic scaling perturbation (added to an anisotropic scaling of one)
`--shear`	Double		(optional) specify the sampling standard deviation of the anisotropic shear perturbation
`--shift`	Double		(optional) specify the sampling standard deviation of the translational shift perturbation
`--deformEffect`	Double	`3.0`	(optional) specify the amount of deform
`--deformExtent`	Double	`10.0`	(optional) specify the extent of deform
`--deformIters`	Integer	`10`	(optional) specify the number of deformation integration iterations
`--deformRandomize`	Double	`0.0`	(optional) randomize the amount of deform with the given sample standard deviation

Output:

Flag	Type	Description
`--outputVolume`	Volume	(optional) output volume
`--outputDeform`	Deformation	(optional) output deformation field
`--outputAffine`	Affine	(optional) output affine transform
`--outputTable`	Table	(optional) output table

VolumePerturbSignal

Perturb the volume signal for data augmentation

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--blend`	Volume	(optional) input blending volume

Parameters:

Flag	Type	Default	Description
`--blendMean`	Double	`0.0`	(optional) specify the blending factor sampling mean value
`--blendStd`	Double	`0.0`	(optional) specify the averaging factor sampling standard deviation
`--noise`	Double	`0.0`	(optional) specify the sampling standard deviation of the intensity noise perturbation
`--biasMean`	Double	`0.0`	(optional) specify the sampling mean of the bias field perturbation
`--biasStd`	Double	`0.0`	(optional) specify the sampling standard deviation of the bias field perturbation
`--contrastMean`	Double	`0.0`	(optional) specify the sampling mean of the contrast perturbation (zero is no change)
`--contrastStd`	Double	`0.0`	(optional) specify the sampling standard deviation of the contrast perturbation (zero is no change)

Output:

Flag	Type	Description
`--outputVolume`	Volume	(optional) output volume
`--outputTable`	Table	(optional) output table

VolumePhantomBox

Create a simple box phantom

Parameters:

Flag	Type	Default	Description
`--width`	int	`100`	(optional) image width
`--height`	int	`100`	(optional) image height
`--slices`	int	`1`	(optional) image slices
`--size`	double	`0.5`	(optional) box relative dimensions

Output:

Flag	Type	Description
`--output`	Volume	output volume

VolumePoseCopy

Set the pose (orientation and origin) of a volume to match a reference volume

Input:

Flag	Type	Description
`--input`	Volume	the input volume
`--ref`	Volume	the reference volume (the pose will be copied from here)

Parameters:

Flag	Type	Default	Description
`--delta`	flag		(optional) copy the voxel spacing as well

Output:

Flag	Type	Description
`--output`	Volume	the output volume

VolumePoseGet

Get the pose (orientation and origin) of a volume

Input:

Flag	Type	Description
`--input`	Volume	the input volume

Output:

Flag	Type	Description
`--output`	Affine	the output affine xfm

VolumePoseSet

Set the pose (orientation and origin) of a volume. By default, the existing origin and orientation will be removed

Input:

Flag	Type	Description
`--input`	Volume	the input volume
`--pose`	Affine	the affine pose (any shear will be removed)

Parameters:

Flag	Type	Default	Description
`--premult`	flag		(optional) compose the existing pose with the given one by premultiplying
`--postmult`	flag		(optional) compose the existing pose with the given one by post multiplying

Output:

Flag	Type	Description
`--output`	Volume	the output volume

VolumePrintInfo

Print basic information about a volume

Input:

Flag	Type	Description
`--input`	Volume	the input volume

Parameters:

Flag	Type	Default	Description
`--stats`	flag		(optional) print statistics
`--nifti`	flag		(optional) print complete nifti header (only relevant if the input is nifti)

VolumeProjection

Compute a projection of an image volume along one axis, for example a minimum intensity projection

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--axis`	VolumeProjectionAxis	`k`	(optional) the axis for the projection (Options: i, j, k)
`--type`	VolumeProjectionType	`Mean`	(optional) the type of statistic for the projection (Options: Min, Max, Mean, Sum, Var, CV, Median, IQR)
`--thin`	Integer		(optional) use thin projection, whereby groups of the given number of slices are aggregated
`--index`	int	`0`	(optional) when collapsing the volume to a single slice, use this image index for the position

Output:

Flag	Type	Description
`--output`	Volume	output image slice

VolumePrototype

Crop a volume down to a smaller volume (only one criteria per run)

Input:

Flag	Type	Description
`--input`	Volume	input volume

Parameters:

Flag	Type	Default	Description
`--dim`	Integer		the output volume dimension

Output:

Flag	Type	Description
`--output`	Volume	the output volume

VolumeReduce

Reduce a multi-channel volume to a volume with fewer channels

Input:

Flag	Type	Description
`--input`	Volume	input volume

Parameters:

Flag	Type	Default	Description
`--which`	String		(optional) the list of indices to select (comma separated zero-based indices)
`--exclude`	String		(optional) exclude specific indices (comma separated zero-based indices)
`--method`	VolumeReduceType	`Mean`	(optional) specify the reduction technique (Subset depends on which or exclude flags) (Options: Subset, Mean, Min, Max, Sum, Var, Std, Gray, RGB)

Output:

Flag	Type	Description
`--output`	Volume	output volume

VolumeRegionMinima

Mask a volume

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--regions`	Mask	a mask encoding regions
`--lookup`	Table	a table encoding region names
`--mask`	Mask	(optional) a mask restricting which voxels are checked

Parameters:

Flag	Type	Default	Description
`--minimum`	flag		(optional) retain the minimum value
`--sample`	flag		(optional) retain the sample voxel indices
`--index`	String	`index`	(optional) specify the lookup index field
`--name`	String	`name`	(optional) specify the lookup name field
`--min`	String	`min`	(optional) specify the output field name for the minimum value
`--i`	String	`i`	(optional) specify the output field name for the sample i index
`--j`	String	`j`	(optional) specify the output field name for the sample j index
`--k`	String	`k`	(optional) specify the output field name for the sample k index

Output:

Flag	Type	Description
`--output`	Table	output table

VolumeRegisterLinear

Estimate an affine transform between two volumes

Input:

Flag	Type	Description
`--input`	Volume	input moving volume, which is registered to the reference volume
`--ref`	Volume	the reference volume
`--mask`	Mask	(optional) a mask used to exclude a portion of the input volume
`--refmask`	Mask	(optional) a mask used to exclude a portion of the reference volume

Parameters:

Flag	Type	Default	Description
`--init`	VolumeRegisterLinearInit	`Center`	(optional) the type of initialization (Options: World, Center, CenterSize)

Output:

Flag	Type	Description
`--output`	Affine	output transform

VolumeRemoveNaN

Remove NaN values

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--replace`	Double	`0.0`	(optional) the value to replace

Output:

Flag	Type	Description
`--output`	Volume	the output volume

VolumeRender

Render a volume slice based on a colormap

Input:

Flag	Type	Description
`--background`	Volume	(optional) input background
`--foreground`	Volume	(optional) input foreground colored using a scalar colormap
`--labels`	Mask	(optional) input labels colored using a discrete colormap
`--fgmask`	Mask	(optional) input foreground mask
`--bgmask`	Mask	(optional) input background mask

Parameters:

Flag	Type	Default	Description
`--range`	String	`all`	(optional) input slice range, e.g. :,:,80
`--bgmap`	String	`grayscale`	(optional) background colormap
`--bglow`	String	`0`	(optional) background lower bound (supports statistics like min, max, etc)
`--bghigh`	String	`1`	(optional) background upper bound (supports statistics like min, max, etc)
`--fgmap`	String	`grayscale`	(optional) scalar colormap for coloring the volume
`--fglow`	String	`0`	(optional) scalar lower bound (supports statistics like min, max, etc)
`--fghigh`	String	`1`	(optional) scalar upper bound (supports statistics like min, max, etc)
`--fgrlow`	String	`0`	(optional) scalar lower bound for range (0 to 1)
`--fgrhigh`	String	`1`	(optional) scalar upper bound for range (0 to 1)
`--discrete`	String	`White`	(optional) discrete colormap for coloring the label volume
`--invert`	flag		(optional) invert colormap
`--wash`	double	`0.0`	(optional) wash out colors
`--alpha`	double	`1.0`	(optional) blending of background with foreground
`--label`	String	`attribute`	(optional) a label for the colormap

Output:

Flag	Type	Description
`--output`	Volume	(optional) output RGB volume rendering
`--colormap`	Volume	(optional) output RGB colormap rendering

VolumeReorder

Change the ordering of voxels in a volume. You can flip and shift the voxels. Which shifting outside the field a view, the data is wrapped around. Shifting is applied before flipping

Input:

Flag	Type	Description
`--input`	Volume	input volume

Parameters:

Flag	Type	Default	Description
`--flipi`	flag		(optional) flip in i
`--flipj`	flag		(optional) flip in j
`--flipk`	flag		(optional) flip in k
`--shifti`	int	`0`	(optional) shift in i
`--shiftj`	int	`0`	(optional) shift in j
`--shiftk`	int	`0`	(optional) shift in k
`--swapij`	flag		(optional) swap ij
`--swapik`	flag		(optional) swap ik
`--swapjk`	flag		(optional) swap jk

Output:

Flag	Type	Description
`--output`	Volume	output volume

VolumeResample

Resample a volume with a different voxel size

Input:

Flag	Type	Description
`--input`	Volume	the input volume

Parameters:

Flag	Type	Default	Description
`--dx`	double	`1.0`	(optional) the voxel size in x
`--dy`	double	`1.0`	(optional) the voxel size in y
`--dz`	double	`1.0`	(optional) the voxel size in z
`--interp`	InterpolationType	`Trilinear`	(optional) image interpolation method (Options: Nearest, Trilinear, Tricubic, Gaussian, GaussianLocalLinear, GaussianLocalQuadratic)

Output:

Flag	Type	Description
`--output`	Volume	the output volume

VolumeResliceACPC

Reslice a volume using ACPC alignment (anterior and posterior commissure). You must provide a vects object with three points for the AC, PC, and another midline position (order must match)

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--acpcmid`	Vects	a vects containing three points: the anterior commisure, the posterior commissure, and any other midline point that is superior to the AC-PC axis
`--bounds`	Vects	(optional) points that bound the region of interest (by default the whole volume will be used)

Parameters:

Flag	Type	Default	Description
`--delta`	Double		(optional) the voxel spacing (by default it detects it from the input)
`--interp`	InterpolationType	`Trilinear`	(optional) image interpolation method (Options: Nearest, Trilinear, Tricubic, Gaussian, GaussianLocalLinear, GaussianLocalQuadratic)

Output:

Flag	Type	Description
`--output`	Volume	output volume

VolumeResliceAxis

Reslice a volume along a given axis (specified by a vects)

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--vects`	Vects	(optional) input vects (should roughly lie on a straight line)
`--mask`	Mask	(optional) input mask

Parameters:

Flag	Type	Default	Description
`--delta`	Double		(optional) the voxel spacing (by default it detects it from the input)
`--mode`	VolumeResliceMode	`K`	(optional) specify the target slice (Options: I, J, K)
`--interp`	InterpolationType	`Trilinear`	(optional) image interpolation method (Options: Nearest, Trilinear, Tricubic, Gaussian, GaussianLocalLinear, GaussianLocalQuadratic)

Output:

Flag	Type	Description
`--output`	Volume	output volume

VolumeReslicePlane

Reslice a volume by a given plane (contained in a solids object)

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--plane`	Solids	input solids (should contain a plane)
`--mask`	Mask	(optional) input mask

Parameters:

Flag	Type	Default	Description
`--delta`	Double		(optional) the voxel spacing (by default it detects it from the input)
`--mode`	VolumeResliceMode	`K`	(optional) specify the target slice (Options: I, J, K)
`--interp`	InterpolationType	`Trilinear`	(optional) image interpolation method (Options: Nearest, Trilinear, Tricubic, Gaussian, GaussianLocalLinear, GaussianLocalQuadratic)

Output:

Flag	Type	Description
`--output`	Volume	output volume

VolumeSampleCortex

Estimate cortical gray matter parameters

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mesh`	Mesh	input mesh
`--mask`	Mask	(optional) a mask
`--gm`	Volume	(optional) input gray matter probability map

Parameters:

Flag	Type	Default	Description
`--name`	String	`data`	(optional) the name of the volumetric data (only used for naming mesh attributes)
`--pial`	String	`pial`	(optional) pial attribute name
`--middle`	String	`middle`	(optional) the middle attribute name
`--white`	String	`white`	(optional) white attribute name
`--samples`	int	`15`	(optional) the number of points to sample
`--inner`	double	`0.0`	(optional) the inner search buffer size
`--outer`	double	`0.0`	(optional) the outer search buffer size
`--linear`	flag		(optional) use linear weights, e.g. 1 - abs(x)
`--gain`	double	`12.0`	(optional) use the given weight gain, e.g. exp(-gain*x^2))
`--zscore`	Double	`3.0`	(optional) the z-score for filtering
`--mest`	flag		(optional) use Tukey’s biweight m-estimator for robust statistics

Output:

Flag	Type	Description
`--output`	Mesh	(optional) the output mesh
`--weights`	Volume	(optional) the output weights
`--num`	Vects	(optional) the output num vects
`--median`	Vects	(optional) the output mean vects
`--mean`	Vects	(optional) the output mean vects
`--std`	Vects	(optional) the output std vects
`--min`	Vects	(optional) the output min vects
`--max`	Vects	(optional) the output max vects

VolumeSampleLine

Sample a volume along a polyline. The results are stored in table along with the world coordinates and position along the segment

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--vects`	Vects	input vects (two points in a vects object)
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--num`	int	`5`	(optional) the number of samples
`--interp`	InterpolationType	`Trilinear`	(optional) image interpolation method (Options: Nearest, Trilinear, Tricubic, Gaussian, GaussianLocalLinear, GaussianLocalQuadratic)
`--value`	String	`value`	(optional) the name of the volume value field
`--vector`	flag		(optional) include vector values

Advanced Parameters:

Flag	Type	Default	Description
`--dims`	String		(optional) a which of dimensions to use
`--vx`	String	`x`	(optional) the field for the x coordinate
`--vy`	String	`y`	(optional) the field for the y coordinate
`--vz`	String	`z`	(optional) the field for the z coordinate
`--pos`	String	`posCamera`	(optional) the position along the line segment in mm
`--idx`	String	`idx`	(optional) the index along the line segment

Output:

Flag	Type	Description
`--output`	Table	output table

VolumeSegmentCluster

Segment a volume by clustering intensities (with k-means, dp-means, or Gaussian mixtures)

Input:

Flag	Type	Description
`--input`	Volume	the input volume
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--iters`	int	`10`	(optional) a maximum number of iterations
`--num`	int	`3`	(optional) the number classes (inital guess in the case of dp-means)
`--restarts`	int	`1`	(optional) the number of restarts
`--lambda`	Double		(optional) a threshold for detecting the number of clusters in the DP-means algorithm
`--bayesian`	flag		(optional) use a Bayesian probabilistic approach (MRF Gaussian mixture expectation maximization framework)
`--emIters`	Integer	`5`	(optional) use the following number of expectation maximization iteration
`--emCov`	String	`spherical`	(optional) specify a covariance type (spherical, diagonal, full)
`--emReg`	Double	`0.0`	(optional) a regularization parameter added to the covariance
`--mrfIters`	Integer	`5`	(optional) use the following number of MRF optimization iterations
`--mrfCross`	flag		(optional) use a 6-neighborhood (instead of a full 27-neighborhood with diagonals)
`--mrfGamma`	Double	`1.0`	(optional) use the following spatial regularization weight
`--mrfCrfGain`	Double	`1.0`	(optional) use the gain used for the conditional random field (zero will disable it)

Output:

Flag	Type	Description
`--labels`	Mask	the output label map
`--membership`	Volume	the output membership map

VolumeSegmentForeground

Segment the foreground of a volume using a statistical approach

Input:

Flag	Type	Description
`--input`	Volume	input volume

Parameters:

Flag	Type	Default	Description
`--median`	Integer	`1`	(optional) the number of times to median prefilter
`--thresh`	Double		(optional) apply a threshold
`--fill`	flag		(optional) fill the foreground mask to remove islands
`--largest`	flag		(optional) extract the largest island
`--mrf`	flag		(optional) apply markov random field spatial regularization
`--mrfCross`	flag		(optional) use a 6-neighborhood (instead of a full 27-neighborhood with diagonals)
`--mrfGamma`	Double	`1.0`	(optional) use the following spatial regularization weight
`--mrfCrfGain`	Double	`1.0`	(optional) use the gain used for the conditional random field (zero will disable it)
`--mrfIcmIters`	Integer	`5`	(optional) use the following number of MRF optimization iterations
`--mrfEmIters`	Integer	`5`	(optional) use the following number of expectation maximization iteration

Output:

Flag	Type	Description
`--output`	Mask	(optional) the output mask
`--report`	Table	(optional) the output report

VolumeSegmentForegroundOtsu

Segment the foreground of a volume using the Otsu method

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--median`	int	`3`	(optional) apply a median filter this many times before segmenting
`--open`	int	`2`	(optional) open the mask with mask morphology
`--islands`	flag		(optional) keep islands in the segmentation (otherwise only the largest component is kept)
`--holes`	flag		(optional) keep holes in the segmentation (otherwise they will be filled)
`--dilate`	int	`0`	(optional) dilate the segmentation at the very end
`--threads`	int	`1`	(optional) use this many threads

Output:

Flag	Type	Description
`--output`	Mask	the output mask

VolumeSegmentGraph

Segment a volume using graph based segmentation

Input:

Flag	Type	Description
`--input`	Volume	the input tensor volume
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--min`	Integer	`10`	(optional) a minima region size
`--threshold`	Double	`1.0`	(optional) a threshold for grouping

Output:

Flag	Type	Description
`--output`	Mask	the output segmentation mask

Citation: Felzenszwalb, P. F., & Huttenlocher, D. P. (2004). Efficient graph-based image segmentation. International journal of computer vision, 59(2), 167-181. Chicago

VolumeSegmentLocalExtrema

Segment a volume based on local extrema

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mask`	Mask	(optional) input mask

Parameters:

Flag	Type	Default	Description
`--minima`	flag		(optional) find minima instead of maxima
`--full`	flag		(optional) use a full 27-voxel neighborhood (default is 6-voxel)

Output:

Flag	Type	Description
`--output`	Mask	output region labels

VolumeSegmentRegionGrowing

Segment a volume using a statistical region-growing technique

Input:

Flag	Type	Description
`--input`	Volume	the input volume
`--seed`	Mask	the input seed mask
`--include`	Mask	(optional) an option mask for including only specific voxels in the segmentation
`--exclude`	Mask	(optional) an option for excluding voxels from the segmentation

Parameters:

Flag	Type	Default	Description
`--nbThresh`	int	`0`	(optional) the neighbor count threshold
`--dataThresh`	Double	`3.0`	(optional) the intensity stopping threshold
`--gradThresh`	Double	`3.0`	(optional) the gradient stopping threshold
`--maxiter`	int	`10000`	(optional) the maxima number of iterations
`--maxsize`	double	`1.7976931348623157E308`	(optional) the maxima region volume
`--full`	flag		(optional) use a full 27-voxel neighborhood (default is 6-voxel)

Output:

Flag	Type	Description
`--output`	Mask	the output segmentation

Citation: Adams, R., & Bischof, L. (1994). Seeded region growing. IEEE Transactions on pattern analysis and machine intelligence, 16(6), 641-647.

VolumeSegmentSuperKMeans

Segment supervoxels from a volume using k-means. Voxels are clustered based on position and intensity

Input:

Flag	Type	Description
`--input`	Volume	the input volume
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--iters`	int	`10`	(optional) a maxima number of iterations
`--num`	int	`100`	(optional) the number regions
`--scale`	double	`1.0`	(optional) the scaleCamera for combining intensities with voxel positions

Output:

Flag	Type	Description
`--output`	Mask	none

VolumeSegmentSuperSLIC

Segment a volume to obtain SLIC supervoxels

Input:

Flag	Type	Description
`--input`	Volume	the input volume
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--iters`	int	`500`	(optional) a maximum number of iterations
`--error`	double	`0.001`	(optional) the convergence criteria
`--size`	double	`20.0`	(optional) the average size (along each dimension) for the supervoxels
`--scale`	double	`1.0`	(optional) the scaleCamera for intensities
`--merge`	double	`10.0`	(optional) a threshold region volume for merging
`--group`	Double		(optional) a threshold gradient magnitude for grouping

Output:

Flag	Type	Description
`--output`	Mask	none

Citation: Radhakrishna Achanta, Appu Shaji, Kevin Smith, Aurelien Lucchi, Pascal Fua, and Sabine Susstrunk, SLIC Superpixels, EPFL Technical Report 149300, June 2010.

VolumeSetGrid

Standardize the orientation of a volume (no rotation and zero origin). The original pose can be saved to xfm.

Input:

Flag	Type	Description
`--input`	Volume	input Volume

Parameters:

Flag	Type	Description
`--df`	Double	(optional) scale the delta by the given factor
`--dx`	Double	(optional) set the x delta
`--dy`	Double	(optional) set the y delta
`--dz`	Double	(optional) set the z delta
`--sf`	Double	(optional) scale the voxel origin by the given factor
`--sx`	Double	(optional) set the x origin (delta)
`--sy`	Double	(optional) set the y origin (delta)
`--sz`	Double	(optional) set the z origin (delta)

Output:

Flag	Type	Description
`--output`	Volume	(optional) output Volume

VolumeSetSampling

Set the origin of a volume

Input:

Flag	Type	Description
`--input`	Volume	the input volume

Parameters:

Flag	Type	Description
`--starti`	Double	(optional) the origin in i
`--startj`	Double	(optional) the origin in j
`--startk`	Double	(optional) the origin in k
`--deltai`	Double	(optional) the voxel spacing in i
`--deltaj`	Double	(optional) the voxel spacing in j
`--deltak`	Double	(optional) the voxel spacing in k

Output:

Flag	Type	Description
`--output`	Volume	the output volume

VolumeSetTable

Create a table listing regions of a mask

Input:

Flag	Type	Description
`--reference`	Volume	input volume
`--table`	Table	input table

Parameters:

Flag	Type	Default	Description
`--dim`	int	`0`	(optional) the channel
`--index`	String	`index`	(optional) the index field name
`--value`	String	`value`	(optional) a field to set
`--background`	double	`0.0`	(optional) a background value
`--missing`	Double		(optional) a missing value

Output:

Flag	Type	Description
`--output`	Volume	output volume

VolumeSkeletonize

Extract a skeleton from the local maxima and ridges of a volume

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mask`	Mask	(optional) input mask

Parameters:

Flag	Type	Default	Description
`--threshold`	Double		(optional) exclude voxels with an input intensity below this value

Output:

Flag	Type	Description
`--output`	Mask	output skeleton

VolumeSlice

Threshold a volume to make a mask

Input:

Flag	Type	Description
`--input`	Volume	input volume

Parameters:

Flag	Type	Default	Description
`--slice`	int	`0`	(optional) a slice number
`--dim`	String	`z`	(optional) a slice channel (x, y, or z)

Output:

Flag	Type	Description
`--output`	Volume	output volume

VolumeSliceMesh

Create a mesh from image slices

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mask`	Mask	(optional) input mask

Parameters:

Flag	Type	Default	Description
`--attribute`	String	`data`	(optional) specify a name for the attribute
`--range`	String	`start:25:end`	(optional) specify a range of slices to extract (or a specific slice)
`--axis`	VolumeSliceMeshAxis	`k`	(optional) the slice axis (Options: i, j, k)
`--nobg`	flag		(optional) remove background voxels
`--thresh`	double	`1.0E-6`	(optional) specify a threshold for background removal
`--color`	flag		(optional) add vertex colors
`--normalize`	flag		(optional) use min/max normalization

Output:

Flag	Type	Description
`--output`	Mesh	output mesh

VolumeSmtFit

Estimate microscopic diffusion parameters

Input:

Flag	Type	Description
`--input`	Volume	the input diffusion-weighted MR volume
`--gradients`	Gradients	the input gradients
`--mask`	Mask	(optional) the input mask

Parameters:

Flag	Type	Default	Description
`--threads`	int	`1`	(optional) the input number of threads

Advanced Parameters:

Flag	Type	Default	Description
`--maxiter`	int	`5000`	(optional) the maximum number of iterations
`--rhobeg`	double	`0.1`	(optional) the starting simplex size
`--rhoend`	double	`1.0E-6`	(optional) the ending simplex size
`--dperp`	double	`5.0E-4`	(optional) the initial guess for perpendicular diffusivity
`--dpar`	double	`0.0017`	(optional) the initial guess for parallel diffusivity
`--dmax`	double	`0.003`	(optional) the maximum diffusivity

Output:

Flag	Type	Description
`--output`	Volume	the output parameter map

Citation: Kaden, E., Kruggel, F., & Alexander, D. C. (2016). Quantitative mapping of the per-axon diffusion coefficients in brain white matter. Magnetic resonance in medicine, 75(4), 1752-1763.

VolumeSort

Sort two volumes based on their mean intensity

Input:

Flag	Type	Description
`--a`	Volume	input volume a
`--b`	Volume	input volume b
`--mask`	Mask	(optional) input mask

Output:

Flag	Type	Description
`--outputLow`	Volume	output low volume
`--outputHigh`	Volume	output high volume

VolumeSortChannels

Sort the channels of a multi-channel volumes based on their mean intensity

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mask`	Mask	(optional) input mask

Parameters:

Flag	Type	Default	Description
`--reverse`	flag		(optional) reverse the order (output will be decreasing)

Output:

Flag	Type	Description
`--output`	Volume	output

VolumeSpharmODF

Sample an orientation distribution function (ODF) from a spharm volume.

Input:

Flag	Type	Description
`--input`	Volume	the input spharm volume
`--points`	Vects	(optional) the sphere points for estimation
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--num`	Integer	`300`	(optional) the number of points to use if you need to generate spherical points
`--threads`	Integer	`1`	(optional) the number of threads in the pool

Output:

Flag	Type	Description
`--output`	Volume	the output odf volume
`--outpoints`	Vects	(optional) the output odf directions (only relevant if you didn’t provide a specific set)

VolumeSpharmPeaks

Extract the peaks from a spherical harmonic volume. This finds the average direction of local maxima clustered by hierarchical clustering. The output fibers will encode the peak q-value in place of volume fraction.

Input:

Flag	Type	Description
`--input`	Volume	the input spharm volume
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--comps`	Integer	`4`	(optional) the maximum number of comps
`--thresh`	Double	`0.1`	(optional) the minimum peak threshold
`--detail`	Integer	`7`	(optional) the level of detail for spherical harmonic sampling
`--mode`	PeakMode	`Mean`	(optional) the mode for extracting the peak fraction from the lobe (Options: Sum, Mean, Max)
`--cluster`	Double	`25.0`	(optional) the minimum angle in degrees for hierarchical clustering of local maxima
`--match`	flag		(optional) match the ODF sum
`--threads`	Integer	`1`	(optional) the number of threads in the pool

Output:

Flag	Type	Description
`--output`	Volume	the output fibers volume

VolumeStackParticles

Extract particles from an image stack. This is meant to process datasets that are too big to be fully loaded into memory. This will process one slice at a time and save the results to disk in the process.

Parameters:

Flag	Type	Default	Description
`--input`	String	`slice%04d.tif`	(optional) input filename pattern (e.g. %04d will be replaced with 0000, 0001, etc. or e.g. %d will be replaced with 0, 1, etc.)
`--isize`	double	`1.0`	(optional) the voxel size in the i direction
`--jsize`	double	`1.0`	(optional) the voxel size in the j direction
`--ksize`	double	`1.0`	(optional) the voxel size in the k direction
`--istart`	int	`0`	(optional) start at the given pixel in i when reading the volume
`--jstart`	int	`0`	(optional) start at the given pixel in j when reading the volume
`--kstart`	int	`0`	(optional) start at the given pixel in k when reading the volume
`--istep`	int	`1`	(optional) step the given number of pixels in i when reading the volume
`--jstep`	int	`1`	(optional) step the given number of pixels in j when reading the volume
`--kstep`	int	`1`	(optional) step the given number of pixels in k when reading the volume
`--samples`	Double	`8.0`	(optional) the number of particle samples per unit intensity (e.g. if the image intensity is one, it will produce this many particles)
`--min`	double	`0.25`	(optional) specify a minimum window intensity (all voxels below this intensity are ignored)
`--max`	double	`0.75`	(optional) specify a maximum window intensity (all voxels above this intensity are sampled uniformly)
`--empty`	flag		(optional) keep empty particle slices
`--dstart`	int	`0`	(optional) start at the given index when loading slices
`--dend`	Integer		(optional) end at the given index when loading slices
`--dstep`	int	`1`	(optional) step the given amount when loading slices
`--interp`	InterpolationType	`Nearest`	(optional) use the given image interpolation method (Options: Nearest, Trilinear, Tricubic, Gaussian, GaussianLocalLinear, GaussianLocalQuadratic)
`--output`	String	`output.csv`	(optional) output filename of particles (should end in csv)

VolumeStackProject

Compute the maximum or minimum intensity projection of an image stack

Parameters:

Flag	Type	Default	Description
`--input`	String	`input/slice%04d.png`	(optional) input filename pattern (e.g. %04d will be replaced with 0000, 0001, etc. or e.g. %d will be replaced with 0, 1, etc.)
`--min`	flag		(optional) use a minimum intensity projection (default is maximum intensity projection)
`--mode`	ProjectMode	`FullZ`	(optional) project slabs of a given stack fraction (only relevant to SlabFracZ) (Options: FullZ, SlabZ, SlabFracZ, FullX, FullY)
`--statistic`	StatisticMode	`Max`	(optional) the statistic to use for projection (Options: Max, Min, Mean, Sum)
`--slabCount`	Integer	`100`	(optional) project slabs of a given thickness (only relevant to SlabZ)
`--slabStep`	Integer	`100`	(optional) use a given step amount (only relevant to the SlabZ)
`--slabFraction`	Double	`0.1`	(optional) project slabs of a given stack fraction (only relevant to SlabFracZ)
`--xstart`	int	`0`	(optional) start at the given index projecting pixels in x
`--xend`	Integer		(optional) end at the given index projecting pixels in x
`--ystart`	int	`0`	(optional) start at the given index projecting pixels in y
`--yend`	Integer		(optional) end at the given index projecting pixels in y
`--dstart`	int	`0`	(optional) start at the given index when loading slices
`--dend`	Integer		(optional) end at the given index when loading slices
`--dstep`	int	`1`	(optional) step the given amount when loading slices
`--output`	String	`output.png`	(optional) the output stack (use %d if you specify a slab)

VolumeStackRead

Read a volume from an image stack

Parameters:

Flag	Type	Default	Description
`--input`	String	`%03d.tif`	(optional) the input filename input for reading each image (must contain %d or some a similar formatting charater for substituting the index)
`--isize`	double	`1.0`	(optional) the voxel size in the i direction
`--jsize`	double	`1.0`	(optional) the voxel size in the j direction
`--ksize`	double	`1.0`	(optional) the voxel size in the k direction
`--istart`	int	`0`	(optional) start at the given pixel in i when reading the volume
`--jstart`	int	`0`	(optional) start at the given pixel in j when reading the volume
`--kstart`	int	`0`	(optional) start at the given pixel in k when reading the volume
`--istep`	int	`1`	(optional) step the given number of pixels in i when reading the volume
`--jstep`	int	`1`	(optional) step the given number of pixels in j when reading the volume
`--kstep`	int	`1`	(optional) step the given number of pixels in k when reading the volume
`--dstart`	int	`0`	(optional) start at the given index when loading slices
`--dend`	Integer		(optional) end at the given index when loading slices
`--dstep`	int	`1`	(optional) step the given amount when loading slices
`--smooth`	Double		(optional) apply Gaussian smoothing to each slice with the given bandwidth in pixels (before downsampling)

Output:

Flag	Type	Description
`--output`	Volume	output volume

VolumeStackReadBlocks

Extract particles from an image stack. This is meant to process datasets that are too big to be fully loaded into memory. This will process one slice at a time and save the results to disk in the process.

Parameters:

Flag	Type	Default	Description
`--input`	String	`/your/path/input/block%04d.nii.gz`	(optional) input block filename pattern (e.g. %04d will be replaced with 0000, 0001, etc. or e.g. %d will be replaced with 0, 1, etc.)
`--ref`	String	`/your/path/ref/slice%04d.png`	(optional) reference image stack filename pattern (e.g. %04d will be replaced with 0000, 0001, etc. or e.g. %d will be replaced with 0, 1, etc.)
`--isize`	int	`256`	(optional) the block size in the i direction
`--jsize`	int	`256`	(optional) the block size in the j direction
`--ksize`	int	`64`	(optional) the voxel size in the k direction
`--overlap`	int	`8`	(optional) the amount of overlap in blocks
`--scale`	double	`1.0`	(optional) the scaling applied to the image intensities
`--dstart`	int	`0`	(optional) start at the given index when loading slices
`--dend`	Integer		(optional) end at the given index when loading slices
`--dstep`	int	`1`	(optional) step the given amount when loading slices
`--output`	String	`/your/path/output/slice%04d.png`	(optional) output image stack filename pattern (e.g. %04d will be replaced with 0000, 0001, etc. or e.g. %d will be replaced with 0, 1, etc.)

VolumeStackWrite

Save the volume to an image stack

Input:

Flag	Type	Description
`--input`	Volume	input volume

Parameters:

Flag	Type	Default	Description
`--output`	String		output directory to the stack
`--axis`	VolumeSaveStackAxis	`k`	(optional) choose an axis for slicing (Options: i, j, k)
`--range`	String		(optional) specify a range, e.g. ‘10:50,5:25,start:2:end’
`--enhance`	flag		(optional) enhance the contrast
`--pattern`	String	`slice%04d.png`	(optional) the output pattern for saving each image

VolumeStackWriteBlocks

Extract particles from an image stack. This is meant to process datasets that are too big to be fully loaded into memory. This will process one slice at a time and save the results to disk in the process.

Parameters:

Flag	Type	Default	Description
`--input`	String	`/your/path/slice%04d.tif`	(optional) input image stack filename pattern (e.g. %04d will be replaced with 0000, 0001, etc. or e.g. %d will be replaced with 0, 1, etc.)
`--isize`	int	`256`	(optional) the block size in the i direction
`--jsize`	int	`256`	(optional) the block size in the j direction
`--ksize`	int	`64`	(optional) the voxel size in the k direction
`--overlap`	int	`8`	(optional) the amount of overlap in blocks
`--idelta`	double	`1.0`	(optional) the voxel size in the i direction
`--jdelta`	double	`1.0`	(optional) the voxel size in the j direction
`--kdelta`	double	`1.0`	(optional) the voxel delta in the k direction
`--dstart`	int	`0`	(optional) start at the given index when loading slices
`--dend`	Integer		(optional) end at the given index when loading slices
`--dstep`	int	`1`	(optional) step the given amount when loading slices
`--output`	String	`/your/path/output%04d.nii.gz`	(optional) output block filename pattern (e.g. %04d will be replaced with 0000, 0001, etc. or e.g. %d will be replaced with 0, 1, etc.)

VolumeStandardize

Standardize the orientation of a volume (no rotation and zero origin). The original pose can be saved to xfm.

Input:

Flag	Type	Description
`--input`	Volume	input Volume

Output:

Flag	Type	Description
`--output`	Volume	(optional) output Volume
`--xfm`	Affine	(optional) output affine
`--invxfm`	Affine	(optional) output inverse affine

VolumeStatsPaired

Compute pairwise statistics from volumetric data

Input:

Flag	Type	Description
`--matching`	Table	a table where each row stores a pair of matching subjects

Parameters:

Flag	Type	Default	Description
`--pattern`	String		input volume filename pattern (should contain %s for the subject identifier)
`--left`	String	`left`	(optional) the left group in the pair
`--right`	String	`right`	(optional) the right group in the pair

Output:

Flag	Type	Description
`--outputLeftMean`	Volume	(optional) output left mean volume
`--outputLeftStd`	Volume	(optional) output left standard deviation volume
`--outputRightMean`	Volume	(optional) output right mean volume
`--outputRightStd`	Volume	(optional) output right standard deviation volume
`--outputDiff`	Volume	(optional) output difference in means
`--outputCohenD`	Volume	(optional) output Cohen’s-d effect size

VolumeStoreVoxelPosition

Create a volume storing the 3D world coordinates of each voxel

Input:

Flag	Type	Description
`--input`	Volume	the input volume

Output:

Flag	Type	Description
`--output`	Volume	output volume

VolumeSubset

Which the intensities of a volume

Input:

Flag	Type	Description
`--input`	Volume	input volume

Parameters:

Flag	Type	Default	Description
`--which`	String		the list of indices to select

Output:

Flag	Type	Description
`--output`	Volume	output volume

VolumeSurfacePlot

Plot data from a planar image

Input:

Flag	Type	Description
`--input`	Volume	input
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--dimension`	int	`0`	(optional) the channel
`--sx`	double	`1.0`	(optional) the scaleCamera in x
`--sy`	double	`1.0`	(optional) the scaleCamera in y
`--sz`	double	`1.0`	(optional) the scaleCamera in z

Output:

Flag	Type	Description
`--output`	Mesh	output

VolumeTable

Record voxel values in a table

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mask`	Mask	(optional) a mask
`--lookup`	Table	(optional) a lookup table for matching names to mask labels

Parameters:

Flag	Type	Default	Description
`--value`	String	`value`	(optional) value
`--multiple`	flag		(optional) use multiple mask labels

Advanced Parameters:

Flag	Type	Default	Description
`--lookupNameField`	String	`name`	(optional) specify the lookup name field
`--lookupIndexField`	String	`voxel`	(optional) specify the output voxel field name
`--range`	String		(optional) a mask specification
`--dims`	String		(optional) a which of dimensions to use
`--vector`	flag		(optional) include vector values
`--vi`	String		(optional) the field for the voxel i coordinate
`--vj`	String		(optional) the field for the voxel j coordinate
`--vk`	String		(optional) the field for the voxel k coordinate
`--voxel`	String	`voxel`	(optional) the field for the voxel voxel

Output:

Flag	Type	Description
`--output`	Table	output table

VolumeTensorFilter

Filter a tensor volume in a variety of ways, e.g. changing units, clamping diffusivities, masking out regions

Input:

Flag	Type	Description
`--input`	Volume	the input tensor volume

Parameters:

Flag	Type	Description
`--scale`	Double	(optional) the scaleCamera to multiply diffusivities (typically needed to changed the physical units)
`--clamp`	Double	(optional) clamp the diffusivities (values below the threshold will be set to it)
`--expression`	String	(optional) zero out voxels that do not satisfy the given arithmetic expression, e.g. FA > 0.15 && MD < 0.001 && MD > 0.0001

Output:

Flag	Type	Description
`--output`	Volume	the output tensor volume

VolumeTensorFit

Fit a tensor volume to a diffusion-weighted MRI.

Input:

Flag	Type	Description
`--input`	Volume	input diffusion-weighted MR volume
`--gradients`	Gradients	the gradients
`--mask`	Mask	(optional) the mask

Parameters:

Flag	Type	Default	Description
`--method`	TensorFitType	`LLS`	(optional) specify an estimation method (Options: LLS, WLLS, NLLS, FWLLS, FWWLLS, FWNLLS, RESTORE)

Advanced Parameters:

Flag	Type	Default	Description
`--cost`	CostType	`SE`	(optional) specify a cost function for non-linear fitting (Options: SE, MSE, RMSE, NRMSE, CHISQ, RLL)
`--single`	flag		(optional) use the lowest single shell for tensor estimation (if used, this will skip the shells, which, and exclude flags)
`--bestb`	flag		(optional) use the best combination of b-values (first try b<=1250, and otherwise use the lowest single shell)
`--rounder`	Integer	`100`	(optional) specify the multiple for rounding b-values, e.g. if the rounder in 100, then 1233 is treated as 1200
`--shells`	String		(optional) specify a subset of gradient shells to include (comma-separated list of b-values)
`--which`	String		(optional) specify a subset of gradients to include (comma-separated list of indices starting from zero)
`--exclude`	String		(optional) specify a subset of gradients to exclude (comma-separated list of indices starting from zero)
`--baseline`	flag		(optional) estimate the baseline value separately from tensor parameter estimation (only for LLS)
`--threads`	int	`1`	(optional) the number of threads to use
`--clamp`	Double	`0.0`	(optional) clamp the diffusivity to be greater or equal to the given value

Output:

Flag	Type	Description
`--output`	Volume	output tensor volume (name output like *.dti and an directory of volumes will be created)

VolumeTensorNoise

Add noise to a tensor volume

Input:

Flag	Type	Description
`--input`	Volume	input tensor volume
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--sigma`	Double		(optional) the sigma of the noise

Output:

Flag	Type	Description
`--output`	Volume	output tensor volume

VolumeTensorOdf

Sample an orientation distribution function (ODF) from a tensor volume.

Input:

Flag	Type	Description
`--input`	Volume	the input tensor volume
`--dirs`	Vects	the sphere directions
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--alpha`	Double	`1.0`	(optional) the alpha power value
`--threads`	Integer	`1`	(optional) the number of threads in the pool

Output:

Flag	Type	Description
`--output`	Volume	the output odf volume

VolumeTensorSegmentGraph

Tensor volume graph-based segmentation based on principal direction

Input:

Flag	Type	Description
`--input`	Volume	the input tensor volume
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--line`	flag		(optional) use a line metric
`--log`	flag		(optional) use a log Euclidean metric
`--threshold`	Double	`1.0`	(optional) a threshold for grouping

Output:

Flag	Type	Description
`--output`	Mask	the output segmentation mask

VolumeTensorSegmentSuper

Segment supervoxels from a tensor volume

Input:

Flag	Type	Description
`--input`	Volume	the input tensor volume
`--mask`	Mask	a mask
`--weights`	Volume	(optional) a weight volume

Parameters:

Flag	Type	Default	Description
`--size`	Integer		(optional) a threshold size (any region smaller than this will be removed)
`--iters`	Integer	`10`	(optional) the number of iterations
`--restarts`	Integer		(optional) the number of restarts
`--num`	Integer	`100`	(optional) the number of clusters (the initial number if dp-means is used)
`--alpha`	Double	`1.0`	(optional) the alpha parameter for spatial extent
`--beta`	Double	`15.0`	(optional) the beta parameter for angular extent
`--lambda`	Double		(optional) the lambda parameter for region size (for dp-means clustering)

Output:

Flag	Type	Description
`--output`	Mask	the output segmentation mask

VolumeTensorSegmentTissue

Use a free-water eliminated tensor volume to segment gray and white matter

Input:

Flag	Type	Description
`--input`	Volume	the input tensor volume
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--fw`	Double	`0.5`	(optional) a maximum free water
`--md`	Double	`2.0E-4`	(optional) a minimum mean diffusivity
`--num`	Integer	`2`	(optional) a number of iterations for mask opening

Output:

Flag	Type	Description
`--labels`	Mask	the gray matter segmentation mask
`--gray`	Volume	the gray matter density map
`--white`	Volume	the white matter density map

VolumeTensorSmooth

Smooth a tensor volume

Input:

Flag	Type	Description
`--input`	Volume	the input tensor volume
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--support`	Integer	`3`	(optional) the filter radius in voxels
`--hpos`	Double	`1.0`	(optional) the positional bandwidth in mm
`--hdir`	Double		(optional) the tensor adaptive bandwidth
`--hsig`	Double		(optional) the baseline signal adaptive bandwidth
`--log`	flag		(optional) use log-euclidean processing
`--frac`	Double	`0.0`	(optional) exclude voxels below a give FA

Output:

Flag	Type	Description
`--output`	Volume	the output tensor volume

VolumeTensorStandardize

Standardize the pose of a tensor volume. This will remove the rotation and tranlation from the image grid and rotate the tensors accordingly

Input:

Flag	Type	Description
`--input`	Volume	the input tensor volume

Output:

Flag	Type	Description
`--output`	Volume	the output transformed tensor volume
`--xfm`	Affine	(optional) output affine xfm
`--invxfm`	Affine	(optional) output inverse affine xfm

VolumeTensorThreshold

Create a mask from a tensor volume using a complex expression

Input:

Flag	Type	Description
`--input`	Volume	the input tensor volume
`--mask`	Mask	(optional) mask

Parameters:

Flag	Type	Default	Description
`--expression`	String	`FA > 0.15 && MD < 0.001 && MD > 0.0001`	(optional) the expression to evaluate

Output:

Flag	Type	Description
`--output`	Mask	output mask

VolumeTensorTransform

Spatially transform a tensor volume

Input:

Flag	Type	Description
`--input`	Volume	the input tensor volume
`--reference`	Volume	input reference volume
`--mask`	Mask	(optional) input mask (defined in the reference space)
`--inputMask`	Mask	(optional) use an input mask (defined in the input space)
`--affine`	Affine	(optional) apply an affine xfm
`--invaffine`	Affine	(optional) apply an inverse affine xfm
`--deform`	Deformation	(optional) apply a deformation xfm

Parameters:

Flag	Type	Default	Description
`--reverse`	flag		(optional) reverse the order, i.e. compose the affine(deform(x)), whereas the default is deform(affine(x))
`--reorient`	ReorientationType	`Jacobian`	(optional) specify a reorient method (fs or jac) (Options: FiniteStrain, Jacobian)
`--interp`	KernelInterpolationType	`Trilinear`	(optional) the interpolation type (Options: Nearest, Trilinear, Gaussian)
`--support`	Integer	`3`	(optional) the filter radius in voxels
`--hpos`	Double	`1.0`	(optional) the positional bandwidth in mm
`--log`	flag		(optional) use log estimation

Output:

Flag	Type	Description
`--output`	Volume	the output transformed tensor volume

VolumeTensorZoom

Zoom a tensor volume

Input:

Flag	Type	Description
`--input`	Volume	the input tensor volume
`--mask`	Mask	(optional) a mask

Parameters:

Flag	Type	Default	Description
`--factor`	double	`2.0`	(optional) a zooming factor
`--interp`	KernelInterpolationType	`Trilinear`	(optional) the interpolation type (Options: Nearest, Trilinear, Gaussian)
`--log`	flag		(optional) use log euclidean estimation
`--support`	Integer	`3`	(optional) the filter radius in voxels
`--hpos`	Double	`2.0`	(optional) the positional bandwidth in mm

Output:

Flag	Type	Description
`--output`	Volume	the output tensor volume

VolumeThreshold

Threshold a volume to make a mask

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mask`	Mask	(optional) mask

Parameters:

Flag	Type	Default	Description
`--threshold`	Double	`0.5`	(optional) threshold value
`--magnitude`	flag		(optional) use the magnitude for multi-channel volumes
`--invert`	flag		(optional) invert the threshold
`--prenorm`	flag		(optional) normalize the intensities to unit mean before thresholding

Output:

Flag	Type	Description
`--output`	Mask	output mask

VolumeThresholdHysteresis

Apply a hysteresis threshold

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mask`	Mask	(optional) mask

Parameters:

Flag	Type	Default	Description
`--low`	Double	`0.5`	(optional) this low threshold value
`--high`	Double	`0.75`	(optional) the high threshold value
`--magnitude`	flag		(optional) use the magnitude for multi-channel volumes
`--invert`	flag		(optional) invert the threshold
`--prenorm`	flag		(optional) normalize the intensities to unit mean before thresholding

Output:

Flag	Type	Description
`--output`	Mask	output mask

VolumeThresholdOtsu

Threshold a volume using Otsu’s method

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mask`	Mask	(optional) mask

Parameters:

Flag	Type	Default	Description
`--bins`	int	`512`	(optional) the number of bins
`--invert`	flag		(optional) invert the segmentation

Output:

Flag	Type	Description
`--output`	Mask	output mask

Citation: Nobuyuki Otsu (1979). “A threshold selection method from gray-level histograms”. IEEE Trans. Sys., Man., Cyber. 9 (1): 62-66.

VolumeThresholdRamp

Threshold a volume using a ramp defined by low and high thresholds. Values below the low threshold will be zero, values above will be one, and ones in between will increase gradually.

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mask`	Mask	(optional) mask

Parameters:

Flag	Type	Default	Description
`--low`	double	`0.25`	(optional) low threshold value
`--high`	double	`0.25`	(optional) low threshold value
`--magnitude`	flag		(optional) use the magnitude for multi-channel volumes
`--invert`	flag		(optional) invert the threshold

Output:

Flag	Type	Description
`--output`	Volume	output threshold map

VolumeThresholdRange

Threshold a volume to make a mask

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--mask`	Mask	(optional) mask

Parameters:

Flag	Type	Default	Description
`--lower`	Double	`0.25`	(optional) threshold value
`--upper`	Double	`0.75`	(optional) threshold value
`--magnitude`	flag		(optional) use the magnitude for multi-channel volumes
`--invert`	flag		(optional) invert the threshold
`--prenorm`	flag		(optional) normalize the intensities to unit mean before thresholding

Output:

Flag	Type	Description
`--output`	Mask	output mask

VolumeTiffPrintInfo

Print info about the organization of a TIFF file

Parameters:

Flag	Type	Description
`--input`	String	the filename of the input volume
`--which`	String	(optional) print info only about a specific sub-page
`--table`	flag	(optional) write the summary as a table

VolumeTiffSplit

Print info about the organization of a TIFF file

Parameters:

Flag	Type	Description
`--input`	String	the filename of the input tiff file
`--output`	String	the filename pattern of the output tiffs (should contain %d)
`--which`	String	(optional) extract only a specific sub-page (comma-separated list)

VolumeTile

Tile a collection of volumes in a single volume

Parameters:

Flag	Type	Default	Description
`--pattern`	String	`volume.${x}.${y}.nii.gz`	(optional) the input pattern (should contain ${x} and ${y})
`--xids`	String	`a,b,c`	(optional) the row identifiers to be substituted
`--yids`	String	`1,2,3,4`	(optional) the column identifiers to be substituted
`--xbuffer`	int	`0`	(optional) a buffer size between tiles
`--ybuffer`	int	`0`	(optional) a buffer size between tiles
`--orientation`	String	`z`	(optional) slice orientation for storing a stack (x, y, or z)

Output:

Flag	Type	Description
`--output`	Volume	the output volume

VolumeTransfer

Apply a transfer function to a volume

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--transfer`	Table	input transfer function (table with from and to fields)

Parameters:

Flag	Type	Default	Description
`--from`	String	`from`	(optional) the from field name
`--to`	String	`to`	(optional) the to field name

Output:

Flag	Type	Description
`--output`	Volume	output

VolumeTransform

Transform a volume

Input:

Flag	Type	Description
`--input`	Volume	input volume
`--reference`	Volume	input reference volume
`--mask`	Mask	(optional) use a mask (defined in the reference space)
`--inputMask`	Mask	(optional) use an input mask (defined in the input space)
`--affine`	Affine	(optional) apply an affine xfm
`--invaffine`	Affine	(optional) apply an inverse affine xfm
`--deform`	Deformation	(optional) apply a deformation xfm

Parameters:

Flag	Type	Default	Description
`--interp`	InterpolationType	`Trilinear`	(optional) image interpolation method (Options: Nearest, Trilinear, Tricubic, Gaussian, GaussianLocalLinear, GaussianLocalQuadratic)
`--reverse`	flag		(optional) reverse the order, i.e. compose the affine(deform(x)), whereas the default is deform(affine(x))
`--reorient`	flag		(optional) reorient vector image data
`--reoriention`	ReorientationType	`Jacobian`	(optional) specify a reorient method (fs or jac) (Options: FiniteStrain, Jacobian)
`--threads`	Integer	`1`	(optional) the number of threads in the pool

Output:

Flag	Type	Description
`--output`	Volume	output volume

VolumeVoxelMathScalar

Evaluate an expression at each voxel of volume data

Input:

Flag	Type	Description
`--a`	Volume	the input volume stored as a variable named ‘a’
`--b`	Volume	(optional) the input volume stored as a variable named ‘b’
`--c`	Volume	(optional) the input volume stored as a variable named ‘c’
`--d`	Volume	(optional) the input volume stored as a variable named ‘d’
`--mask`	Mask	(optional) mask

Parameters:

Flag	Type	Default	Description
`--expression`	String	`a > 0.5`	(optional) the expression to evaluate
`--undefined`	double	`0.0`	(optional) use the specificed value for undefined output, e.g. NaN or Infinity

Output:

Flag	Type	Description
`--output`	Volume	output volume

VolumeVoxelMathVect

Evaluate an expression at each voxel of volume data

Input:

Flag	Type	Description
`--a`	Volume	the input volume stored as a variable named ‘a’
`--b`	Volume	(optional) the input volume stored as a variable named ‘b’
`--c`	Volume	(optional) the input volume stored as a variable named ‘c’
`--d`	Volume	(optional) the input volume stored as a variable named ‘d’
`--mask`	Mask	(optional) mask

Parameters:

Flag	Type	Default	Description
`--world`	flag		(optional) add a variable for world coordinates of the given voxel
`--expression`	String	`mean(a)`	(optional) the expression to evaluate
`--undefined`	double	`0.0`	(optional) use the specified value for undefined output, e.g. NaN or Infinity

Output:

Flag	Type	Description
`--output`	Volume	output volume

VolumeZoom

Zoom a volume. Note: be careful using this for downsampling, as it does not apply an anti-aliasing prefilter.

Input:

Flag	Type	Description
`--input`	Volume	the input volume

Parameters:

Flag	Type	Default	Description
`--factor`	Double		(optional) an isotropic scaling factor
`--fi`	Double		(optional) a scaling factor in i
`--fj`	Double		(optional) a scaling factor in j
`--fk`	Double		(optional) a scaling factor in k
`--interp`	InterpolationType	`Trilinear`	(optional) an interpolation type (Options: Nearest, Trilinear, Tricubic, Gaussian, GaussianLocalLinear, GaussianLocalQuadratic)
`--threads`	Integer	`3`	(optional) the number of threads in the pool

Output:

Flag	Type	Description
`--output`	Volume	the output volume