nipype.interfaces.niftyseg.maths module

Nipype interface for seg_maths.

The maths module provides higher-level interfaces to some of the operations that can be performed with the niftysegmaths (seg_maths) command-line program.

BinaryMaths

Link to code

Bases: MathsCommand

Wrapped executable: seg_maths.

Binary mathematical operations.

See also

Source code – Documentation

Examples

>>> import copy
>>> from nipype.interfaces import niftyseg
>>> binary = niftyseg.BinaryMaths()
>>> binary.inputs.in_file = 'im1.nii'
>>> binary.inputs.output_datatype = 'float'

>>> # Test sub operation
>>> binary_sub = copy.deepcopy(binary)
>>> binary_sub.inputs.operation = 'sub'
>>> binary_sub.inputs.operand_file = 'im2.nii'
>>> binary_sub.cmdline
'seg_maths im1.nii -sub im2.nii -odt float im1_sub.nii'
>>> binary_sub.run()  

>>> # Test mul operation
>>> binary_mul = copy.deepcopy(binary)
>>> binary_mul.inputs.operation = 'mul'
>>> binary_mul.inputs.operand_value = 2.0
>>> binary_mul.cmdline
'seg_maths im1.nii -mul 2.00000000 -odt float im1_mul.nii'
>>> binary_mul.run()  

>>> # Test llsnorm operation
>>> binary_llsnorm = copy.deepcopy(binary)
>>> binary_llsnorm.inputs.operation = 'llsnorm'
>>> binary_llsnorm.inputs.operand_file = 'im2.nii'
>>> binary_llsnorm.cmdline
'seg_maths im1.nii -llsnorm im2.nii -odt float im1_llsnorm.nii'
>>> binary_llsnorm.run()  

>>> # Test splitinter operation
>>> binary_splitinter = copy.deepcopy(binary)
>>> binary_splitinter.inputs.operation = 'splitinter'
>>> binary_splitinter.inputs.operand_str = 'z'
>>> binary_splitinter.cmdline
'seg_maths im1.nii -splitinter z -odt float im1_splitinter.nii'
>>> binary_splitinter.run()  

Mandatory Inputs:

• in_file (a pathlike object or string representing an existing file) – Image to operate on. Maps to a command-line argument: %s (position: 2).

• operand_file (a pathlike object or string representing an existing file) – Second image to perform operation with. Maps to a command-line argument: %s (position: 5). Mutually exclusive with inputs: operand_value, operand_str.

• operand_str (‘x’ or ‘y’ or ‘z’) – String value to perform operation splitinter. Maps to a command-line argument: %s (position: 5). Mutually exclusive with inputs: operand_value, operand_file.

• operand_value (a float) – Float value to perform operation with. Maps to a command-line argument: %.8f (position: 5). Mutually exclusive with inputs: operand_file, operand_str.

• operation (‘mul’ or ‘div’ or ‘add’ or ‘sub’ or ‘pow’ or ‘thr’ or ‘uthr’ or ‘smo’ or ‘edge’ or ‘sobel3’ or ‘sobel5’ or ‘min’ or ‘smol’ or ‘geo’ or ‘llsnorm’ or ‘masknan’ or ‘hdr_copy’ or ‘splitinter’) –

  Operation to perform:

  • mul - <float/file> - Multiply image <float> value or by other image.

  • div - <float/file> - Divide image by <float> or by other image.

  • add - <float/file> - Add image by <float> or by other image.

  • sub - <float/file> - Subtract image by <float> or by other image.

  • pow - <float> - Image to the power of <float>.

  • thr - <float> - Threshold the image below <float>.

  • uthr - <float> - Threshold image above <float>.

  • smo - <float> - Gaussian smoothing by std <float> (in voxels and up to 4-D).

  • edge - <float> - Calculate the edges of the image using a threshold <float>.

  • sobel3 - <float> - Calculate the edges of all timepoints using a Sobel filter with a 3x3x3 kernel and applying <float> gaussian smoothing.

  • sobel5 - <float> - Calculate the edges of all timepoints using a Sobel filter with a 5x5x5 kernel and applying <float> gaussian smoothing.

  • min - <file> - Get the min per voxel between <current> and <file>.

  • smol - <float> - Gaussian smoothing of a 3D label image.

  • geo - <float/file> - Geodesic distance according to the speed function <float/file>

  • llsnorm <file_norm> - Linear LS normalisation between current and <file_norm>

  • masknan <file_norm> - Assign everything outside the mask (mask==0) with NaNs

  • hdr_copy <file> - Copy header from working image to <file> and save in <output>.

  • splitinter <x/y/z> - Split interleaved slices in direction <x/y/z> into separate time points

  Maps to a command-line argument: -%s (position: 4).

Optional Inputs:

• args (a string) – Additional parameters to the command. Maps to a command-line argument: %s.

• environ (a 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: {})

• out_file (a pathlike object or string representing a file) – Image to write. Maps to a command-line argument: %s (position: -2).

• output_datatype (‘float’ or ‘char’ or ‘int’ or ‘short’ or ‘double’ or ‘input’) – Datatype to use for output (default uses input type). Maps to a command-line argument: -odt %s (position: -3).

Outputs:

out_file (a pathlike object or string representing a file) – Image written after calculations.

BinaryMathsInteger

Link to code

Bases: MathsCommand

Wrapped executable: seg_maths.

Integer mathematical operations.

See also

Source code – Documentation

Examples

>>> import copy
>>> from nipype.interfaces.niftyseg import BinaryMathsInteger
>>> binaryi = BinaryMathsInteger()
>>> binaryi.inputs.in_file = 'im1.nii'
>>> binaryi.inputs.output_datatype = 'float'
>>> # Test dil operation
>>> binaryi_dil = copy.deepcopy(binaryi)
>>> binaryi_dil.inputs.operation = 'dil'
>>> binaryi_dil.inputs.operand_value = 2
>>> binaryi_dil.cmdline
'seg_maths im1.nii -dil 2 -odt float im1_dil.nii'
>>> binaryi_dil.run()  
>>> # Test dil operation
>>> binaryi_ero = copy.deepcopy(binaryi)
>>> binaryi_ero.inputs.operation = 'ero'
>>> binaryi_ero.inputs.operand_value = 1
>>> binaryi_ero.cmdline
'seg_maths im1.nii -ero 1 -odt float im1_ero.nii'
>>> binaryi_ero.run()  
>>> # Test pad operation
>>> binaryi_pad = copy.deepcopy(binaryi)
>>> binaryi_pad.inputs.operation = 'pad'
>>> binaryi_pad.inputs.operand_value = 4
>>> binaryi_pad.cmdline
'seg_maths im1.nii -pad 4 -odt float im1_pad.nii'
>>> binaryi_pad.run()  

Mandatory Inputs:

• in_file (a pathlike object or string representing an existing file) – Image to operate on. Maps to a command-line argument: %s (position: 2).

• operand_value (an integer) – Int value to perform operation with. Maps to a command-line argument: %d (position: 5).

• operation (‘dil’ or ‘ero’ or ‘tp’ or ‘equal’ or ‘pad’ or ‘crop’) –

  Operation to perform:

  • equal - <int> - Get voxels equal to <int>

  • dil - <int> - Dilate the image <int> times (in voxels).

  • ero - <int> - Erode the image <int> times (in voxels).

  • tp - <int> - Extract time point <int>

  • crop - <int> - Crop <int> voxels around each 3D volume.

  • pad - <int> - Pad <int> voxels with NaN value around each 3D volume.

  Maps to a command-line argument: -%s (position: 4).

Optional Inputs:

• args (a string) – Additional parameters to the command. Maps to a command-line argument: %s.

• environ (a 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: {})

• out_file (a pathlike object or string representing a file) – Image to write. Maps to a command-line argument: %s (position: -2).

• output_datatype (‘float’ or ‘char’ or ‘int’ or ‘short’ or ‘double’ or ‘input’) – Datatype to use for output (default uses input type). Maps to a command-line argument: -odt %s (position: -3).

Outputs:

out_file (a pathlike object or string representing a file) – Image written after calculations.

MathsCommand

Link to code

Bases: NiftySegCommand

Wrapped executable: seg_maths.

Base Command Interface for seg_maths interfaces.

The executable seg_maths enables the sequential execution of arithmetic operations, like multiplication (-mul), division (-div) or addition (-add), binarisation (-bin) or thresholding (-thr) operations and convolution by a Gaussian kernel (-smo). It also allows mathematical morphology based operations like dilation (-dil), erosion (-ero), connected components (-lconcomp) and hole filling (-fill), Euclidean (- euc) and geodesic (-geo) distance transforms, local image similarity metric calculation (-lncc and -lssd). Finally, it allows multiple operations over the dimensionality of the image, from merging 3D images together as a 4D image (-merge) or splitting (-split or -tp) 4D images into several 3D images, to estimating the maximum, minimum and average over all time-points, etc.

Mandatory Inputs:

in_file (a pathlike object or string representing an existing file) – Image to operate on. Maps to a command-line argument: %s (position: 2).

Optional Inputs:

• args (a string) – Additional parameters to the command. Maps to a command-line argument: %s.

• environ (a 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: {})

• out_file (a pathlike object or string representing a file) – Image to write. Maps to a command-line argument: %s (position: -2).

• output_datatype (‘float’ or ‘char’ or ‘int’ or ‘short’ or ‘double’ or ‘input’) – Datatype to use for output (default uses input type). Maps to a command-line argument: -odt %s (position: -3).

Outputs:

out_file (a pathlike object or string representing a file) – Image written after calculations.

Merge

Link to code

Bases: MathsCommand

Wrapped executable: seg_maths.

Merge image files.

See also

Source code – Documentation

Examples

>>> from nipype.interfaces import niftyseg
>>> node = niftyseg.Merge()
>>> node.inputs.in_file = 'im1.nii'
>>> files = ['im2.nii', 'im3.nii']
>>> node.inputs.merge_files = files
>>> node.inputs.dimension = 2
>>> node.inputs.output_datatype = 'float'
>>> node.cmdline
'seg_maths im1.nii -merge 2 2 im2.nii im3.nii -odt float im1_merged.nii'

Mandatory Inputs:

• dimension (an integer) – Dimension to merge the images.

• in_file (a pathlike object or string representing an existing file) – Image to operate on. Maps to a command-line argument: %s (position: 2).

• merge_files (a list of items which are a pathlike object or string representing an existing file) – List of images to merge to the working image <input>. Maps to a command-line argument: %s (position: 4).

Optional Inputs:

• args (a string) – Additional parameters to the command. Maps to a command-line argument: %s.

• environ (a 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: {})

• out_file (a pathlike object or string representing a file) – Image to write. Maps to a command-line argument: %s (position: -2).

• output_datatype (‘float’ or ‘char’ or ‘int’ or ‘short’ or ‘double’ or ‘input’) – Datatype to use for output (default uses input type). Maps to a command-line argument: -odt %s (position: -3).

Outputs:

out_file (a pathlike object or string representing a file) – Image written after calculations.

TupleMaths

Link to code

Bases: MathsCommand

Wrapped executable: seg_maths.

Mathematical operations on tuples.

See also

Source code – Documentation

Examples

>>> import copy
>>> from nipype.interfaces import niftyseg
>>> tuple = niftyseg.TupleMaths()
>>> tuple.inputs.in_file = 'im1.nii'
>>> tuple.inputs.output_datatype = 'float'

>>> # Test lncc operation
>>> tuple_lncc = copy.deepcopy(tuple)
>>> tuple_lncc.inputs.operation = 'lncc'
>>> tuple_lncc.inputs.operand_file1 = 'im2.nii'
>>> tuple_lncc.inputs.operand_value2 = 2.0
>>> tuple_lncc.cmdline
'seg_maths im1.nii -lncc im2.nii 2.00000000 -odt float im1_lncc.nii'
>>> tuple_lncc.run()  

>>> # Test lssd operation
>>> tuple_lssd = copy.deepcopy(tuple)
>>> tuple_lssd.inputs.operation = 'lssd'
>>> tuple_lssd.inputs.operand_file1 = 'im2.nii'
>>> tuple_lssd.inputs.operand_value2 = 1.0
>>> tuple_lssd.cmdline
'seg_maths im1.nii -lssd im2.nii 1.00000000 -odt float im1_lssd.nii'
>>> tuple_lssd.run()  

>>> # Test lltsnorm operation
>>> tuple_lltsnorm = copy.deepcopy(tuple)
>>> tuple_lltsnorm.inputs.operation = 'lltsnorm'
>>> tuple_lltsnorm.inputs.operand_file1 = 'im2.nii'
>>> tuple_lltsnorm.inputs.operand_value2 = 0.01
>>> tuple_lltsnorm.cmdline
'seg_maths im1.nii -lltsnorm im2.nii 0.01000000 -odt float im1_lltsnorm.nii'
>>> tuple_lltsnorm.run()  

Mandatory Inputs:

• in_file (a pathlike object or string representing an existing file) – Image to operate on. Maps to a command-line argument: %s (position: 2).

• operand_file1 (a pathlike object or string representing an existing file) – Image to perform operation 1 with. Maps to a command-line argument: %s (position: 5). Mutually exclusive with inputs: operand_value1.

• operand_file2 (a pathlike object or string representing an existing file) – Image to perform operation 2 with. Maps to a command-line argument: %s (position: 6). Mutually exclusive with inputs: operand_value2.

• operand_value1 (a float) – Float value to perform operation 1 with. Maps to a command-line argument: %.8f (position: 5). Mutually exclusive with inputs: operand_file1.

• operand_value2 (a float) – Float value to perform operation 2 with. Maps to a command-line argument: %.8f (position: 6). Mutually exclusive with inputs: operand_file2.

• operation (‘lncc’ or ‘lssd’ or ‘lltsnorm’) –

  Operation to perform:

  • lncc <file> <std> Local CC between current img and <file> on a kernel with <std>

  • lssd <file> <std> Local SSD between current img and <file> on a kernel with <std>

  • lltsnorm <file_norm> <float> Linear LTS normalisation assuming <float> percent outliers

  Maps to a command-line argument: -%s (position: 4).

Optional Inputs:

• args (a string) – Additional parameters to the command. Maps to a command-line argument: %s.

• environ (a 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: {})

• out_file (a pathlike object or string representing a file) – Image to write. Maps to a command-line argument: %s (position: -2).

• output_datatype (‘float’ or ‘char’ or ‘int’ or ‘short’ or ‘double’ or ‘input’) – Datatype to use for output (default uses input type). Maps to a command-line argument: -odt %s (position: -3).

Outputs:

out_file (a pathlike object or string representing a file) – Image written after calculations.

UnaryMaths

Link to code

Bases: MathsCommand

Wrapped executable: seg_maths.

Unary mathematical operations.

See also

Source code – Documentation

Examples

>>> import copy
>>> from nipype.interfaces import niftyseg
>>> unary = niftyseg.UnaryMaths()
>>> unary.inputs.output_datatype = 'float'
>>> unary.inputs.in_file = 'im1.nii'

>>> # Test sqrt operation
>>> unary_sqrt = copy.deepcopy(unary)
>>> unary_sqrt.inputs.operation = 'sqrt'
>>> unary_sqrt.cmdline
'seg_maths im1.nii -sqrt -odt float im1_sqrt.nii'
>>> unary_sqrt.run()  

>>> # Test sqrt operation
>>> unary_abs = copy.deepcopy(unary)
>>> unary_abs.inputs.operation = 'abs'
>>> unary_abs.cmdline
'seg_maths im1.nii -abs -odt float im1_abs.nii'
>>> unary_abs.run()  

>>> # Test bin operation
>>> unary_bin = copy.deepcopy(unary)
>>> unary_bin.inputs.operation = 'bin'
>>> unary_bin.cmdline
'seg_maths im1.nii -bin -odt float im1_bin.nii'
>>> unary_bin.run()  

>>> # Test otsu operation
>>> unary_otsu = copy.deepcopy(unary)
>>> unary_otsu.inputs.operation = 'otsu'
>>> unary_otsu.cmdline
'seg_maths im1.nii -otsu -odt float im1_otsu.nii'
>>> unary_otsu.run()  

>>> # Test isnan operation
>>> unary_isnan = copy.deepcopy(unary)
>>> unary_isnan.inputs.operation = 'isnan'
>>> unary_isnan.cmdline
'seg_maths im1.nii -isnan -odt float im1_isnan.nii'
>>> unary_isnan.run()  

Mandatory Inputs:

• in_file (a pathlike object or string representing an existing file) – Image to operate on. Maps to a command-line argument: %s (position: 2).

• operation (‘sqrt’ or ‘exp’ or ‘log’ or ‘recip’ or ‘abs’ or ‘bin’ or ‘otsu’ or ‘lconcomp’ or ‘concomp6’ or ‘concomp26’ or ‘fill’ or ‘euc’ or ‘tpmax’ or ‘tmean’ or ‘tmax’ or ‘tmin’ or ‘splitlab’ or ‘removenan’ or ‘isnan’ or ‘subsamp2’ or ‘scl’ or ‘4to5’ or ‘range’) –

  Operation to perform:

  • sqrt - Square root of the image).

  • exp - Exponential root of the image.

  • log - Log of the image.

  • recip - Reciprocal (1/I) of the image.

  • abs - Absolute value of the image.

  • bin - Binarise the image.

  • otsu - Otsu thresholding of the current image.

  • lconcomp - Take the largest connected component

  • concomp6 - Label the different connected components with a 6NN kernel

  • concomp26 - Label the different connected components with a 26NN kernel

  • fill - Fill holes in binary object (e.g. fill ventricle in brain mask).

  • euc - Euclidean distance transform

  • tpmax - Get the time point with the highest value (binarise 4D probabilities)

  • tmean - Mean value of all time points.

  • tmax - Max value of all time points.

  • tmin - Mean value of all time points.

  • splitlab - Split the integer labels into multiple timepoints

  • removenan - Remove all NaNs and replace then with 0

  • isnan - Binary image equal to 1 if the value is NaN and 0 otherwise

  • subsamp2 - Subsample the image by 2 using NN sampling (qform and sform scaled)

  • scl - Reset scale and slope info.

  • 4to5 - Flip the 4th and 5th dimension.

  • range - Reset the image range to the min max.

  Maps to a command-line argument: -%s (position: 4).

Optional Inputs:

• args (a string) – Additional parameters to the command. Maps to a command-line argument: %s.

• environ (a 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: {})

• out_file (a pathlike object or string representing a file) – Image to write. Maps to a command-line argument: %s (position: -2).

• output_datatype (‘float’ or ‘char’ or ‘int’ or ‘short’ or ‘double’ or ‘input’) – Datatype to use for output (default uses input type). Maps to a command-line argument: -odt %s (position: -3).

Outputs:

out_file (a pathlike object or string representing a file) – Image written after calculations.