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# nipype.interfaces.ants.utils module

ANTs’ utilities.

## AI

Link to code

> Bases: ANTSCommand

> Wrapped executable: `antsAI`.

> Calculate the optimal linear transform parameters for aligning two images.

> Examples

>     >>> AI(
>     ...     fixed_image='structural.nii',
>     ...     moving_image='epi.nii',
>     ...     metric=('Mattes', 32, 'Regular', 1),
>     ... ).cmdline
>     'antsAI -c [10,1e-06,10] -d 3 -m Mattes[structural.nii,epi.nii,32,Regular,1]
>     -o initialization.mat -p 0 -s [20,0.12] -t Affine[0.1] -v 0'

>     >>> AI(fixed_image='structural.nii',
>     ...    moving_image='epi.nii',
>     ...    metric=('Mattes', 32, 'Regular', 1),
>     ...    search_grid=(12, (1, 1, 1)),
>     ... ).cmdline
>     'antsAI -c [10,1e-06,10] -d 3 -m Mattes[structural.nii,epi.nii,32,Regular,1]
>     -o initialization.mat -p 0 -s [20,0.12] -g [12.0,1x1x1] -t Affine[0.1] -v 0'

> fixed_imagea pathlike object or string representing an existing file

>   Image to which the moving_image should be transformed.

> metrica tuple of the form: (‘Mattes’ or ‘GC’ or ‘MI’, an integer, ‘Regular’ or ‘Random’ or ‘None’, 0.0 <= a floating point number <= 1.0)

>   The metric(s) to use. Maps to a command-line argument: `-m %s`.

> moving_imagea pathlike object or string representing an existing file

>   Image that will be transformed to fixed_image.

> argsa string

>   Additional parameters to the command. Maps to a command-line argument: `%s`.

> convergencea tuple of the form: (1 <= an integer <= 10000, a float, 1 <= an integer <= 100)

>   Convergence. Maps to a command-line argument: `-c [%d,%g,%d]`. (Nipype default value: `(10, 1e-06, 10)`)

> dimension3 or 2

>   Dimension of output image. Maps to a command-line argument: `-d %d`. (Nipype default value: `3`)

> environa dictionary with keys which are a bytes or None or a value of class ‘str’ and with values which are a bytes or None or a value of class ‘str’

>   Environment variables. (Nipype default value: `{}`)

> fixed_image_maska pathlike object or string representing an existing file

>   Fixed mage mask. Maps to a command-line argument: `-x %s`.

> moving_image_maska pathlike object or string representing an existing file

>   Moving mage mask. Requires inputs: `fixed_image_mask`.

> num_threadsan integer

>   Number of ITK threads to use. (Nipype default value: `1`)

> output_transforma pathlike object or string representing a file

>   Output file name. Maps to a command-line argument: `-o %s`. (Nipype default value: `initialization.mat`)

> principal_axesa boolean

>   Align using principal axes. Maps to a command-line argument: `-p %d`. Mutually exclusive with inputs: `blobs`. (Nipype default value: `False`)

> search_factora tuple of the form: (a float, 0.0 <= a floating point number <= 1.0)

>   Search factor. Maps to a command-line argument: `-s [%g,%g]`. (Nipype default value: `(20, 0.12)`)

> search_grida tuple of the form: (a float, a tuple of the form: (a float, a float, a float)) or a tuple of the form: (a float, a tuple of the form: (a float, a float))

>   Translation search grid in mm. Maps to a command-line argument: `-g %s`.

> transforma tuple of the form: (‘Affine’ or ‘Rigid’ or ‘Similarity’, a floating point number > 0.0)

>   Several transform options are available. Maps to a command-line argument: `-t %s[%g]`. (Nipype default value: `('Affine', 0.1)`)

> verbosea boolean

>   Enable verbosity. Maps to a command-line argument: `-v %d`. (Nipype default value: `False`)

> output_transforma pathlike object or string representing an existing file

>   Output file name.

## AffineInitializer

Link to code

> Bases: ANTSCommand

> Wrapped executable: `antsAffineInitializer`.

> Initialize an affine transform (as in antsBrainExtraction.sh)

>     >>> from nipype.interfaces.ants import AffineInitializer
>     >>> init = AffineInitializer()
>     >>> init.inputs.fixed_image = 'fixed1.nii'
>     >>> init.inputs.moving_image = 'moving1.nii'
>     >>> init.cmdline
>     'antsAffineInitializer 3 fixed1.nii moving1.nii transform.mat 15.000000 0.100000 0 10'

> fixed_imagea pathlike object or string representing an existing file

>   Reference image. Maps to a command-line argument: `%s` (position: 1).

> moving_imagea pathlike object or string representing an existing file

>   Moving image. Maps to a command-line argument: `%s` (position: 2).

> argsa string

>   Additional parameters to the command. Maps to a command-line argument: `%s`.

> dimension3 or 2

>   Dimension. Maps to a command-line argument: `%s` (position: 0). (Nipype default value: `3`)

> environa dictionary with keys which are a bytes or None or a value of class ‘str’ and with values which are a bytes or None or a value of class ‘str’

>   Environment variables. (Nipype default value: `{}`)

> local_searchan integer

>   > determines if a local optimization is run at each search point for the set number of iterations.

>   Maps to a command-line argument: `%d` (position: 7). (Nipype default value: `10`)

> num_threadsan integer

>   Number of ITK threads to use. (Nipype default value: `1`)

> out_filea pathlike object or string representing a file

>   Output transform file. Maps to a command-line argument: `%s` (position: 3). (Nipype default value: `transform.mat`)

> principal_axesa boolean

>   Whether the rotation is searched around an initial principal axis alignment. Maps to a command-line argument: `%d` (position: 6). (Nipype default value: `False`)

> radian_fraction0.0 <= a floating point number <= 1.0

>   Search this arc +/- principal axes. Maps to a command-line argument: `%f` (position: 5). (Nipype default value: `0.1`)

> search_factora float

>   Increments (degrees) for affine search. Maps to a command-line argument: `%f` (position: 4). (Nipype default value: `15.0`)

> out_filea pathlike object or string representing a file

>   Output transform file.

## AverageAffineTransform

Link to code

> Bases: ANTSCommand

> Wrapped executable: `AverageAffineTransform`.

> Examples

>     >>> from nipype.interfaces.ants import AverageAffineTransform
>     >>> avg = AverageAffineTransform()
>     >>> avg.inputs.dimension = 3
>     >>> avg.inputs.transforms = ['trans.mat', 'func_to_struct.mat']
>     >>> avg.inputs.output_affine_transform = 'MYtemplatewarp.mat'
>     >>> avg.cmdline
>     'AverageAffineTransform 3 MYtemplatewarp.mat trans.mat func_to_struct.mat'

> dimension3 or 2

>   Image dimension (2 or 3). Maps to a command-line argument: `%d` (position: 0).

> output_affine_transforma pathlike object or string representing a file

>   Outputfname.txt: the name of the resulting transform. Maps to a command-line argument: `%s` (position: 1).

> transformsa list of items which are a pathlike object or string representing an existing file

>   Transforms to average. Maps to a command-line argument: `%s` (position: 3).

> argsa string

>   Additional parameters to the command. Maps to a command-line argument: `%s`.

> environa dictionary with keys which are a bytes or None or a value of class ‘str’ and with values which are a bytes or None or a value of class ‘str’

>   Environment variables. (Nipype default value: `{}`)

> num_threadsan integer

>   Number of ITK threads to use. (Nipype default value: `1`)

> affine_transforma pathlike object or string representing an existing file

>   Average transform file.

## AverageImages

Link to code

> Bases: ANTSCommand

> Wrapped executable: `AverageImages`.

> Examples

>     >>> from nipype.interfaces.ants import AverageImages
>     >>> avg = AverageImages()
>     >>> avg.inputs.dimension = 3
>     >>> avg.inputs.output_average_image = "average.nii.gz"
>     >>> avg.inputs.normalize = True
>     >>> avg.inputs.images = ['rc1s1.nii', 'rc1s1.nii']
>     >>> avg.cmdline
>     'AverageImages 3 average.nii.gz 1 rc1s1.nii rc1s1.nii'

> dimension3 or 2

>   Image dimension (2 or 3). Maps to a command-line argument: `%d` (position: 0).

> imagesa list of items which are a pathlike object or string representing an existing file

>   Image to apply transformation to (generally a coregistered functional). Maps to a command-line argument: `%s` (position: 3).

> normalizea boolean

>   Normalize: if true, the 2nd image is divided by its mean. This will select the largest image to average into. Maps to a command-line argument: `%d` (position: 2).

> argsa string

>   Additional parameters to the command. Maps to a command-line argument: `%s`.

> environa dictionary with keys which are a bytes or None or a value of class ‘str’ and with values which are a bytes or None or a value of class ‘str’

>   Environment variables. (Nipype default value: `{}`)

> num_threadsan integer

>   Number of ITK threads to use. (Nipype default value: `1`)

> output_average_imagea pathlike object or string representing a file

>   The name of the resulting image. Maps to a command-line argument: `%s` (position: 1). (Nipype default value: `average.nii`)

> output_average_imagea pathlike object or string representing an existing file

>   Average image file.

## ComposeMultiTransform

Link to code

> Bases: ANTSCommand

> Wrapped executable: `ComposeMultiTransform`.

> Take a set of transformations and convert them to a single transformation matrix/warpfield.

> Examples

>     >>> from nipype.interfaces.ants import ComposeMultiTransform
>     >>> compose_transform = ComposeMultiTransform()
>     >>> compose_transform.inputs.dimension = 3
>     >>> compose_transform.inputs.transforms = ['struct_to_template.mat', 'func_to_struct.mat']
>     >>> compose_transform.cmdline
>     'ComposeMultiTransform 3 struct_to_template_composed.mat
>     struct_to_template.mat func_to_struct.mat'

> transformsa list of items which are a pathlike object or string representing an existing file

>   Transforms to average. Maps to a command-line argument: `%s` (position: 3).

> argsa string

>   Additional parameters to the command. Maps to a command-line argument: `%s`.

> dimension3 or 2

>   Image dimension (2 or 3). Maps to a command-line argument: `%d` (position: 0). (Nipype default value: `3`)

> environa dictionary with keys which are a bytes or None or a value of class ‘str’ and with values which are a bytes or None or a value of class ‘str’

>   Environment variables. (Nipype default value: `{}`)

> num_threadsan integer

>   Number of ITK threads to use. (Nipype default value: `1`)

> output_transforma pathlike object or string representing a file

>   The name of the resulting transform. Maps to a command-line argument: `%s` (position: 1).

> reference_imagea pathlike object or string representing a file

>   Reference image (only necessary when output is warpfield). Maps to a command-line argument: `%s` (position: 2).

> output_transforma pathlike object or string representing an existing file

>   Composed transform file.

## CreateJacobianDeterminantImage

Link to code

> Bases: ANTSCommand

> Wrapped executable: `CreateJacobianDeterminantImage`.

> Examples

>     >>> from nipype.interfaces.ants import CreateJacobianDeterminantImage
>     >>> jacobian = CreateJacobianDeterminantImage()
>     >>> jacobian.inputs.imageDimension = 3
>     >>> jacobian.inputs.deformationField = 'ants_Warp.nii.gz'
>     >>> jacobian.inputs.outputImage = 'out_name.nii.gz'
>     >>> jacobian.cmdline
>     'CreateJacobianDeterminantImage 3 ants_Warp.nii.gz out_name.nii.gz'

> deformationFielda pathlike object or string representing an existing file

>   Deformation transformation file. Maps to a command-line argument: `%s` (position: 1).

> imageDimension3 or 2

>   Image dimension (2 or 3). Maps to a command-line argument: `%d` (position: 0).

> outputImagea pathlike object or string representing a file

>   Output filename. Maps to a command-line argument: `%s` (position: 2).

> argsa string

>   Additional parameters to the command. Maps to a command-line argument: `%s`.

> doLogJacobian0 or 1

>   Return the log jacobian. Maps to a command-line argument: `%d` (position: 3).

> environa dictionary with keys which are a bytes or None or a value of class ‘str’ and with values which are a bytes or None or a value of class ‘str’

>   Environment variables. (Nipype default value: `{}`)

> num_threadsan integer

>   Number of ITK threads to use. (Nipype default value: `1`)

> useGeometric0 or 1

>   Return the geometric jacobian. Maps to a command-line argument: `%d` (position: 4).

> jacobian_imagea pathlike object or string representing an existing file

>   Jacobian image.

## ImageMath

Link to code

> Bases: ANTSCommand, CopyHeaderInterface

> Wrapped executable: `ImageMath`.

> Operations over images.

> Examples

>     >>> ImageMath(
>     ...     op1='structural.nii',
>     ...     operation='+',
>     ...     op2='2').cmdline
>     'ImageMath 3 structural_maths.nii + structural.nii 2'

>     >>> ImageMath(
>     ...     op1='structural.nii',
>     ...     operation='Project',
>     ...     op2='1 2').cmdline
>     'ImageMath 3 structural_maths.nii Project structural.nii 1 2'

>     >>> ImageMath(
>     ...     op1='structural.nii',
>     ...     operation='G',
>     ...     op2='4').cmdline
>     'ImageMath 3 structural_maths.nii G structural.nii 4'

>     >>> ImageMath(
>     ...     op1='structural.nii',
>     ...     operation='TruncateImageIntensity',
>     ...     op2='0.005 0.999 256').cmdline
>     'ImageMath 3 structural_maths.nii TruncateImageIntensity structural.nii 0.005 0.999 256'

> By default, Nipype copies headers from the first input image (`op1`) to the output image. For some operations, as the `PadImage` operation, the header cannot be copied from inputs to outputs, and so `copy_header` option is automatically set to `False`.

>     >>> pad = ImageMath(
>     ...     op1='structural.nii',
>     ...     operation='PadImage')
>     >>> pad.inputs.copy_header
>     False

> While the operation is set to `PadImage`, setting `copy_header = True` will have no effect.

>     >>> pad.inputs.copy_header = True
>     >>> pad.inputs.copy_header
>     False

> For any other operation, `copy_header` can be enabled/disabled normally:

>     >>> pad.inputs.operation = "ME"
>     >>> pad.inputs.copy_header = True
>     >>> pad.inputs.copy_header
>     True

> op1a pathlike object or string representing an existing file

>   First operator. Maps to a command-line argument: `%s` (position: -3).

> operation‘m’ or ‘vm’ or ‘+’ or ‘v+’ or ‘-’ or ‘v-’ or ‘/’ or ‘^’ or ‘max’ or ‘exp’ or ‘addtozero’ or ‘overadd’ or ‘abs’ or ‘total’ or ‘mean’ or ‘vtotal’ or ‘Decision’ or ‘Neg’ or ‘Project’ or ‘G’ or ‘MD’ or ‘ME’ or ‘MO’ or ‘MC’ or ‘GD’ or ‘GE’ or ‘GO’ or ‘GC’ or ‘ExtractContours’ or ‘Translate’ or ‘4DTensorTo3DTensor’ or ‘ExtractVectorComponent’ or ‘TensorColor’ or ‘TensorFA’ or ‘TensorFADenominator’ or ‘TensorFANumerator’ or ‘TensorMeanDiffusion’ or ‘TensorRadialDiffusion’ or ‘TensorAxialDiffusion’ or ‘TensorEigenvalue’ or ‘TensorToVector’ or ‘TensorToVectorComponent’ or ‘TensorMask’ or ‘Byte’ or ‘CorruptImage’ or ‘D’ or ‘MaurerDistance’ or ‘ExtractSlice’ or ‘FillHoles’ or ‘Convolve’ or ‘Finite’ or ‘FlattenImage’ or ‘GetLargestComponent’ or ‘Grad’ or ‘RescaleImage’ or ‘WindowImage’ or ‘NeighborhoodStats’ or ‘ReplicateDisplacement’ or ‘ReplicateImage’ or ‘LabelStats’ or ‘Laplacian’ or ‘Canny’ or ‘Lipschitz’ or ‘MTR’ or ‘Normalize’ or ‘PadImage’ or ‘SigmoidImage’ or ‘Sharpen’ or ‘UnsharpMask’ or ‘PValueImage’ or ‘ReplaceVoxelValue’ or ‘SetTimeSpacing’ or ‘SetTimeSpacingWarp’ or ‘stack’ or ‘ThresholdAtMean’ or ‘TriPlanarView’ or ‘TruncateImageIntensity’

>   Mathematical operations. Maps to a command-line argument: `%s` (position: 3).

> argsa string

>   Additional parameters to the command. Maps to a command-line argument: `%s` (position: -1).

> copy_headera boolean

>   Copy headers of the original image into the output (corrected) file. (Nipype default value: `True`)

> dimensionan integer

>   Dimension of output image. Maps to a command-line argument: `%d` (position: 1). (Nipype default value: `3`)

> environa dictionary with keys which are a bytes or None or a value of class ‘str’ and with values which are a bytes or None or a value of class ‘str’

>   Environment variables. (Nipype default value: `{}`)

> num_threadsan integer

>   Number of ITK threads to use. (Nipype default value: `1`)

> op2a pathlike object or string representing an existing file or a string

>   Second operator. Maps to a command-line argument: `%s` (position: -2).

> output_imagea pathlike object or string representing a file

>   Output image file. Maps to a command-line argument: `%s` (position: 2).

> output_imagea pathlike object or string representing an existing file

>   Output image file.

## LabelGeometry

Link to code

> Bases: ANTSCommand

> Wrapped executable: `LabelGeometryMeasures`.

> Extracts geometry measures using a label file and an optional image file

> Examples

>     >>> from nipype.interfaces.ants import LabelGeometry
>     >>> label_extract = LabelGeometry()
>     >>> label_extract.inputs.dimension = 3
>     >>> label_extract.inputs.label_image = 'atlas.nii.gz'
>     >>> label_extract.cmdline
>     'LabelGeometryMeasures 3 atlas.nii.gz [] atlas.csv'

>     >>> label_extract.inputs.intensity_image = 'ants_Warp.nii.gz'
>     >>> label_extract.cmdline
>     'LabelGeometryMeasures 3 atlas.nii.gz ants_Warp.nii.gz atlas.csv'

> intensity_imagea pathlike object or string representing an existing file

>   Intensity image to extract values from. This is an optional input. Maps to a command-line argument: `%s` (position: 2). (Nipype default value: `[]`)

> label_imagea pathlike object or string representing a file

>   Label image to use for extracting geometry measures. Maps to a command-line argument: `%s` (position: 1).

> argsa string

>   Additional parameters to the command. Maps to a command-line argument: `%s`.

> dimension3 or 2

>   Image dimension (2 or 3). Maps to a command-line argument: `%d` (position: 0). (Nipype default value: `3`)

> environa dictionary with keys which are a bytes or None or a value of class ‘str’ and with values which are a bytes or None or a value of class ‘str’

>   Environment variables. (Nipype default value: `{}`)

> num_threadsan integer

>   Number of ITK threads to use. (Nipype default value: `1`)

> output_filea string

>   Name of output file. Maps to a command-line argument: `%s` (position: 3).

> output_filea pathlike object or string representing an existing file

>   CSV file of geometry measures.

## MultiplyImages

Link to code

> Bases: ANTSCommand

> Wrapped executable: `MultiplyImages`.

> Examples

>     >>> from nipype.interfaces.ants import MultiplyImages
>     >>> test = MultiplyImages()
>     >>> test.inputs.dimension = 3
>     >>> test.inputs.first_input = 'moving2.nii'
>     >>> test.inputs.second_input = 0.25
>     >>> test.inputs.output_product_image = "out.nii"
>     >>> test.cmdline
>     'MultiplyImages 3 moving2.nii 0.25 out.nii'

> dimension3 or 2

>   Image dimension (2 or 3). Maps to a command-line argument: `%d` (position: 0).

> first_inputa pathlike object or string representing an existing file

>   Image 1. Maps to a command-line argument: `%s` (position: 1).

> output_product_imagea pathlike object or string representing a file

>   Outputfname.nii.gz: the name of the resulting image. Maps to a command-line argument: `%s` (position: 3).

> second_inputa pathlike object or string representing an existing file or a float

>   Image 2 or multiplication weight. Maps to a command-line argument: `%s` (position: 2).

> argsa string

>   Additional parameters to the command. Maps to a command-line argument: `%s`.

> environa dictionary with keys which are a bytes or None or a value of class ‘str’ and with values which are a bytes or None or a value of class ‘str’

>   Environment variables. (Nipype default value: `{}`)

> num_threadsan integer

>   Number of ITK threads to use. (Nipype default value: `1`)

> output_product_imagea pathlike object or string representing an existing file

>   Average image file.

## ResampleImageBySpacing

Link to code

> Bases: ANTSCommand

> Wrapped executable: `ResampleImageBySpacing`.

> Resample an image with a given spacing.

> Examples

>     >>> res = ResampleImageBySpacing(dimension=3)
>     >>> res.inputs.input_image = 'structural.nii'
>     >>> res.inputs.output_image = 'output.nii.gz'
>     >>> res.inputs.out_spacing = (4, 4, 4)
>     >>> res.cmdline
>     'ResampleImageBySpacing 3 structural.nii output.nii.gz 4 4 4'

>     >>> res = ResampleImageBySpacing(dimension=3)
>     >>> res.inputs.input_image = 'structural.nii'
>     >>> res.inputs.output_image = 'output.nii.gz'
>     >>> res.inputs.out_spacing = (4, 4, 4)
>     >>> res.inputs.apply_smoothing = True
>     >>> res.cmdline
>     'ResampleImageBySpacing 3 structural.nii output.nii.gz 4 4 4 1'

>     >>> res = ResampleImageBySpacing(dimension=3)
>     >>> res.inputs.input_image = 'structural.nii'
>     >>> res.inputs.output_image = 'output.nii.gz'
>     >>> res.inputs.out_spacing = (0.4, 0.4, 0.4)
>     >>> res.inputs.apply_smoothing = True
>     >>> res.inputs.addvox = 2
>     >>> res.inputs.nn_interp = False
>     >>> res.cmdline
>     'ResampleImageBySpacing 3 structural.nii output.nii.gz 0.4 0.4 0.4 1 2 0'

> input_imagea pathlike object or string representing an existing file

>   Input image file. Maps to a command-line argument: `%s` (position: 2).

> out_spacinga list of from 2 to 3 items which are a float or a tuple of the form: (a float, a float, a float) or a tuple of the form: (a float, a float)

>   Output spacing. Maps to a command-line argument: `%s` (position: 4).

> addvoxan integer

>   Addvox pads each dimension by addvox. Maps to a command-line argument: `%d` (position: 6). Requires inputs: `apply_smoothing`.

> apply_smoothinga boolean

>   Smooth before resampling. Maps to a command-line argument: `%d` (position: 5).

> argsa string

>   Additional parameters to the command. Maps to a command-line argument: `%s`.

> dimensionan integer

>   Dimension of output image. Maps to a command-line argument: `%d` (position: 1). (Nipype default value: `3`)

> environa dictionary with keys which are a bytes or None or a value of class ‘str’ and with values which are a bytes or None or a value of class ‘str’

>   Environment variables. (Nipype default value: `{}`)

> nn_interpa boolean

>   Nn interpolation. Maps to a command-line argument: `%d` (position: -1). Requires inputs: `addvox`.

> num_threadsan integer

>   Number of ITK threads to use. (Nipype default value: `1`)

> output_imagea pathlike object or string representing a file

>   Output image file. Maps to a command-line argument: `%s` (position: 3).

> output_imagea pathlike object or string representing an existing file

>   Resampled file.

## ThresholdImage

Link to code

> Bases: ANTSCommand, CopyHeaderInterface

> Wrapped executable: `ThresholdImage`.

> Apply thresholds on images.

> Examples

>     >>> thres = ThresholdImage(dimension=3)
>     >>> thres.inputs.input_image = 'structural.nii'
>     >>> thres.inputs.output_image = 'output.nii.gz'
>     >>> thres.inputs.th_low = 0.5
>     >>> thres.inputs.th_high = 1.0
>     >>> thres.inputs.inside_value = 1.0
>     >>> thres.inputs.outside_value = 0.0
>     >>> thres.cmdline
>     'ThresholdImage 3 structural.nii output.nii.gz 0.500000 1.000000 1.000000 0.000000'

>     >>> thres = ThresholdImage(dimension=3)
>     >>> thres.inputs.input_image = 'structural.nii'
>     >>> thres.inputs.output_image = 'output.nii.gz'
>     >>> thres.inputs.mode = 'Kmeans'
>     >>> thres.inputs.num_thresholds = 4
>     >>> thres.cmdline
>     'ThresholdImage 3 structural.nii output.nii.gz Kmeans 4'

> copy_headera boolean

>   Copy headers of the original image into the output (corrected) file. (Nipype default value: `True`)

> input_imagea pathlike object or string representing an existing file

>   Input image file. Maps to a command-line argument: `%s` (position: 2).

> argsa string

>   Additional parameters to the command. Maps to a command-line argument: `%s`.

> dimensionan integer

>   Dimension of output image. Maps to a command-line argument: `%d` (position: 1). (Nipype default value: `3`)

> environa dictionary with keys which are a bytes or None or a value of class ‘str’ and with values which are a bytes or None or a value of class ‘str’

>   Environment variables. (Nipype default value: `{}`)

> input_maska pathlike object or string representing an existing file

>   Input mask for Otsu, Kmeans. Maps to a command-line argument: `%s`. Requires inputs: `num_thresholds`.

> inside_valuea float

>   Inside value. Maps to a command-line argument: `%f` (position: 6). Requires inputs: `th_low`.

> mode‘Otsu’ or ‘Kmeans’

>   Whether to run Otsu / Kmeans thresholding. Maps to a command-line argument: `%s` (position: 4). Mutually exclusive with inputs: `th_low`, `th_high`. Requires inputs: `num_thresholds`.

> num_threadsan integer

>   Number of ITK threads to use. (Nipype default value: `1`)

> num_thresholdsan integer

>   Number of thresholds. Maps to a command-line argument: `%d` (position: 5).

> output_imagea pathlike object or string representing a file

>   Output image file. Maps to a command-line argument: `%s` (position: 3).

> outside_valuea float

>   Outside value. Maps to a command-line argument: `%f` (position: 7). Requires inputs: `th_low`.

> th_higha float

>   Upper threshold. Maps to a command-line argument: `%f` (position: 5). Mutually exclusive with inputs: `mode`.

> th_lowa float

>   Lower threshold. Maps to a command-line argument: `%f` (position: 4). Mutually exclusive with inputs: `mode`.

> output_imagea pathlike object or string representing an existing file

>   Resampled file.