nipype.interfaces.mrtrix.preprocess module

DWI2Tensor

Link to code

Bases: CommandLine

Wrapped executable: dwi2tensor.

Converts diffusion-weighted images to tensor images.

Example

>>> import nipype.interfaces.mrtrix as mrt
>>> dwi2tensor = mrt.DWI2Tensor()
>>> dwi2tensor.inputs.in_file = 'dwi.mif'
>>> dwi2tensor.inputs.encoding_file = 'encoding.txt'
>>> dwi2tensor.cmdline
'dwi2tensor -grad encoding.txt dwi.mif dwi_tensor.mif'
>>> dwi2tensor.run()
Mandatory Inputs

in_file (a list of items which are a pathlike object or string representing an existing file) – Diffusion-weighted images. 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.

  • debug (a boolean) – Display debugging messages. Maps to a command-line argument: -debug (position: 1).

  • encoding_file (a pathlike object or string representing a file) – Encoding file supplied as a 4xN text file with each line is in the format [ X Y Z b ], where [ X Y Z ] describe the direction of the applied gradient, and b gives the b-value in units (1000 s/mm^2). See FSL2MRTrix(). Maps to a command-line argument: -grad %s (position: 2).

  • 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: {})

  • ignore_slice_by_volume (a list of from 2 to 2 items which are an integer) – Requires two values (i.e. [34 1] for [Slice Volume] Ignores the image slices specified when computing the tensor. Slice here means the z coordinate of the slice to be ignored. Maps to a command-line argument: -ignoreslices %s (position: 2).

  • ignore_volumes (a list of at least 1 items which are an integer) – Requires two values (i.e. [2 5 6] for [Volumes] Ignores the image volumes specified when computing the tensor. Maps to a command-line argument: -ignorevolumes %s (position: 2).

  • out_filename (a pathlike object or string representing a file) – Output tensor filename. Maps to a command-line argument: %s (position: -1).

  • quiet (a boolean) – Do not display information messages or progress status. Maps to a command-line argument: -quiet (position: 1).

Outputs

tensor (a pathlike object or string representing an existing file) – Path/name of output diffusion tensor image.

Erode

Link to code

Bases: CommandLine

Wrapped executable: erode.

Erode (or dilates) a mask (i.e. binary) image

Example

>>> import nipype.interfaces.mrtrix as mrt
>>> erode = mrt.Erode()
>>> erode.inputs.in_file = 'mask.mif'
>>> erode.run()
Mandatory Inputs

in_file (a pathlike object or string representing an existing file) – Input mask image to be eroded. 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.

  • debug (a boolean) – Display debugging messages. Maps to a command-line argument: -debug (position: 1).

  • dilate (a boolean) – Perform dilation rather than erosion. Maps to a command-line argument: -dilate (position: 1).

  • 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: {})

  • number_of_passes (an integer) – The number of passes (default: 1). Maps to a command-line argument: -npass %s.

  • out_filename (a pathlike object or string representing a file) – Output image filename. Maps to a command-line argument: %s (position: -1).

  • quiet (a boolean) – Do not display information messages or progress status. Maps to a command-line argument: -quiet (position: 1).

Outputs

out_file (a pathlike object or string representing an existing file) – The output image.

GenerateWhiteMatterMask

Link to code

Bases: CommandLine

Wrapped executable: gen_WM_mask.

Generates a white matter probability mask from the DW images.

Example

>>> import nipype.interfaces.mrtrix as mrt
>>> genWM = mrt.GenerateWhiteMatterMask()
>>> genWM.inputs.in_file = 'dwi.mif'
>>> genWM.inputs.encoding_file = 'encoding.txt'
>>> genWM.run()
Mandatory Inputs

  • binary_mask (a pathlike object or string representing an existing file) – Binary brain mask. Maps to a command-line argument: %s (position: -2).

  • encoding_file (a pathlike object or string representing an existing file) – Gradient encoding, supplied as a 4xN text file with each line is in the format [ X Y Z b ], where [ X Y Z ] describe the direction of the applied gradient, and b gives the b-value in units (1000 s/mm^2). See FSL2MRTrix. Maps to a command-line argument: -grad %s (position: 1).

  • in_file (a pathlike object or string representing an existing file) – Diffusion-weighted images. Maps to a command-line argument: %s (position: -3).

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: {})

  • noise_level_margin (a float) – Specify the width of the margin on either side of the image to be used to estimate the noise level (default = 10). Maps to a command-line argument: -margin %s.

  • out_WMProb_filename (a pathlike object or string representing a file) – Output WM probability image filename. Maps to a command-line argument: %s (position: -1).

Outputs

WMprobabilitymap (a pathlike object or string representing an existing file) – WMprobabilitymap.

MRConvert

Link to code

Bases: CommandLine

Wrapped executable: mrconvert.

Perform conversion between different file types and optionally extract a subset of the input image.

If used correctly, this program can be a very useful workhorse. In addition to converting images between different formats, it can be used to extract specific studies from a data set, extract a specific region of interest, flip the images, or to scale the intensity of the images.

Example

>>> import nipype.interfaces.mrtrix as mrt
>>> mrconvert = mrt.MRConvert()
>>> mrconvert.inputs.in_file = 'dwi_FA.mif'
>>> mrconvert.inputs.out_filename = 'dwi_FA.nii'
>>> mrconvert.run()
Mandatory Inputs

in_file (a pathlike object or string representing an existing file) – Voxel-order data filename. 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: {})

  • extension (‘mif’ or ‘nii’ or ‘float’ or ‘char’ or ‘short’ or ‘int’ or ‘long’ or ‘double’) – “i.e. Bfloat”. Can be “char”, “short”, “int”, “long”, “float” or “double”. (Nipype default value: mif)

  • extract_at_axis (1 or 2 or 3) – “Extract data only at the coordinates specified. This option specifies the Axis. Must be used in conjunction with extract_at_coordinate. Maps to a command-line argument: -coord %s (position: 1).

  • extract_at_coordinate (a list of from 1 to 3 items which are a float) – “Extract data only at the coordinates specified. This option specifies the coordinates. Must be used in conjunction with extract_at_axis. Three comma-separated numbers giving the size of each voxel in mm. Maps to a command-line argument: %s (position: 2).

  • layout (‘nii’ or ‘float’ or ‘char’ or ‘short’ or ‘int’ or ‘long’ or ‘double’) – Specify the layout of the data in memory. The actual layout produced will depend on whether the output image format can support it. Maps to a command-line argument: -output %s (position: 2).

  • offset_bias (a float) – Apply offset to the intensity values. Maps to a command-line argument: -scale %d (position: 3).

  • out_filename (a pathlike object or string representing a file) – Output filename. Maps to a command-line argument: %s (position: -1).

  • output_datatype (‘nii’ or ‘float’ or ‘char’ or ‘short’ or ‘int’ or ‘long’ or ‘double’) – “i.e. Bfloat”. Can be “char”, “short”, “int”, “long”, “float” or “double”. Maps to a command-line argument: -output %s (position: 2).

  • prs (a boolean) – Assume that the DW gradients are specified in the PRS frame (Siemens DICOM only). Maps to a command-line argument: -prs (position: 3).

  • replace_NaN_with_zero (a boolean) – Replace all NaN values with zero. Maps to a command-line argument: -zero (position: 3).

  • resample (a float) – Apply scaling to the intensity values. Maps to a command-line argument: -scale %d (position: 3).

  • voxel_dims (a list of from 3 to 3 items which are a float) – Three comma-separated numbers giving the size of each voxel in mm. Maps to a command-line argument: -vox %s (position: 3).

Outputs

converted (a pathlike object or string representing an existing file) – Path/name of 4D volume in voxel order.

MRMultiply

Link to code

Bases: CommandLine

Wrapped executable: mrmult.

Multiplies two images.

Example

>>> import nipype.interfaces.mrtrix as mrt
>>> MRmult = mrt.MRMultiply()
>>> MRmult.inputs.in_files = ['dwi.mif', 'dwi_WMProb.mif']
>>> MRmult.run()
Mandatory Inputs

in_files (a list of items which are a pathlike object or string representing an existing file) – Input images to be multiplied. 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.

  • debug (a boolean) – Display debugging messages. Maps to a command-line argument: -debug (position: 1).

  • 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_filename (a pathlike object or string representing a file) – Output image filename. Maps to a command-line argument: %s (position: -1).

  • quiet (a boolean) – Do not display information messages or progress status. Maps to a command-line argument: -quiet (position: 1).

Outputs

out_file (a pathlike object or string representing an existing file) – The output image of the multiplication.

MRTransform

Link to code

Bases: CommandLine

Wrapped executable: mrtransform.

Apply spatial transformations or reslice images

Example

>>> MRxform = MRTransform()
>>> MRxform.inputs.in_files = 'anat_coreg.mif'
>>> MRxform.run()
Mandatory Inputs

in_files (a list of items which are a pathlike object or string representing an existing file) – Input images to be transformed. 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.

  • debug (a boolean) – Display debugging messages. Maps to a command-line argument: -debug (position: 1).

  • 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: {})

  • flip_x (a boolean) – Assume the transform is supplied assuming a coordinate system with the x-axis reversed relative to the MRtrix convention (i.e. x increases from right to left). This is required to handle transform matrices produced by FSL’s FLIRT command. This is only used in conjunction with the -reference option. Maps to a command-line argument: -flipx (position: 1).

  • invert (a boolean) – Invert the specified transform before using it. Maps to a command-line argument: -inverse (position: 1).

  • out_filename (a pathlike object or string representing a file) – Output image. Maps to a command-line argument: %s (position: -1).

  • quiet (a boolean) – Do not display information messages or progress status. Maps to a command-line argument: -quiet (position: 1).

  • reference_image (a pathlike object or string representing an existing file) – In case the transform supplied maps from the input image onto a reference image, use this option to specify the reference. Note that this implicitly sets the -replace option. Maps to a command-line argument: -reference %s (position: 1).

  • replace_transform (a boolean) – Replace the current transform by that specified, rather than applying it to the current transform. Maps to a command-line argument: -replace (position: 1).

  • template_image (a pathlike object or string representing an existing file) – Reslice the input image to match the specified template image. Maps to a command-line argument: -template %s (position: 1).

  • transformation_file (a pathlike object or string representing an existing file) – The transform to apply, in the form of a 4x4 ascii file. Maps to a command-line argument: -transform %s (position: 1).

Outputs

out_file (a pathlike object or string representing an existing file) – The output image of the transformation.

MRTrixInfo

Link to code

Bases: CommandLine

Wrapped executable: mrinfo.

Prints out relevant header information found in the image specified.

Example

>>> import nipype.interfaces.mrtrix as mrt
>>> MRinfo = mrt.MRTrixInfo()
>>> MRinfo.inputs.in_file = 'dwi.mif'
>>> MRinfo.run()
Mandatory Inputs

in_file (a pathlike object or string representing an existing file) – Input images to be read. 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: {})

MRTrixViewer

Link to code

Bases: CommandLine

Wrapped executable: mrview.

Loads the input images in the MRTrix Viewer.

Example

>>> import nipype.interfaces.mrtrix as mrt
>>> MRview = mrt.MRTrixViewer()
>>> MRview.inputs.in_files = 'dwi.mif'
>>> MRview.run()
Mandatory Inputs

in_files (a list of items which are a pathlike object or string representing an existing file) – Input images to be viewed. 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.

  • debug (a boolean) – Display debugging messages. Maps to a command-line argument: -debug (position: 1).

  • 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: {})

  • quiet (a boolean) – Do not display information messages or progress status. Maps to a command-line argument: -quiet (position: 1).

MedianFilter3D

Link to code

Bases: CommandLine

Wrapped executable: median3D.

Smooth images using a 3x3x3 median filter.

Example

>>> import nipype.interfaces.mrtrix as mrt
>>> median3d = mrt.MedianFilter3D()
>>> median3d.inputs.in_file = 'mask.mif'
>>> median3d.run()
Mandatory Inputs

in_file (a pathlike object or string representing an existing file) – Input images to be smoothed. 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.

  • debug (a boolean) – Display debugging messages. Maps to a command-line argument: -debug (position: 1).

  • 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_filename (a pathlike object or string representing a file) – Output image filename. Maps to a command-line argument: %s (position: -1).

  • quiet (a boolean) – Do not display information messages or progress status. Maps to a command-line argument: -quiet (position: 1).

Outputs

out_file (a pathlike object or string representing an existing file) – The output image.

Tensor2ApparentDiffusion

Link to code

Bases: CommandLine

Wrapped executable: tensor2ADC.

Generates a map of the apparent diffusion coefficient (ADC) in each voxel

Example

>>> import nipype.interfaces.mrtrix as mrt
>>> tensor2ADC = mrt.Tensor2ApparentDiffusion()
>>> tensor2ADC.inputs.in_file = 'dwi_tensor.mif'
>>> tensor2ADC.run()
Mandatory Inputs

in_file (a pathlike object or string representing an existing file) – Diffusion tensor image. 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.

  • debug (a boolean) – Display debugging messages. Maps to a command-line argument: -debug (position: 1).

  • 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_filename (a pathlike object or string representing a file) – Output Fractional Anisotropy filename. Maps to a command-line argument: %s (position: -1).

  • quiet (a boolean) – Do not display information messages or progress status. Maps to a command-line argument: -quiet (position: 1).

Outputs

ADC (a pathlike object or string representing an existing file) – The output image of the major eigenvectors of the diffusion tensor image.

Tensor2FractionalAnisotropy

Link to code

Bases: CommandLine

Wrapped executable: tensor2FA.

Generates a map of the fractional anisotropy in each voxel.

Example

>>> import nipype.interfaces.mrtrix as mrt
>>> tensor2FA = mrt.Tensor2FractionalAnisotropy()
>>> tensor2FA.inputs.in_file = 'dwi_tensor.mif'
>>> tensor2FA.run()
Mandatory Inputs

in_file (a pathlike object or string representing an existing file) – Diffusion tensor image. 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.

  • debug (a boolean) – Display debugging messages. Maps to a command-line argument: -debug (position: 1).

  • 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_filename (a pathlike object or string representing a file) – Output Fractional Anisotropy filename. Maps to a command-line argument: %s (position: -1).

  • quiet (a boolean) – Do not display information messages or progress status. Maps to a command-line argument: -quiet (position: 1).

Outputs

FA (a pathlike object or string representing an existing file) – The output image of the major eigenvectors of the diffusion tensor image.

Tensor2Vector

Link to code

Bases: CommandLine

Wrapped executable: tensor2vector.

Generates a map of the major eigenvectors of the tensors in each voxel.

Example

>>> import nipype.interfaces.mrtrix as mrt
>>> tensor2vector = mrt.Tensor2Vector()
>>> tensor2vector.inputs.in_file = 'dwi_tensor.mif'
>>> tensor2vector.run()
Mandatory Inputs

in_file (a pathlike object or string representing an existing file) – Diffusion tensor image. 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.

  • debug (a boolean) – Display debugging messages. Maps to a command-line argument: -debug (position: 1).

  • 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_filename (a pathlike object or string representing a file) – Output vector filename. Maps to a command-line argument: %s (position: -1).

  • quiet (a boolean) – Do not display information messages or progress status. Maps to a command-line argument: -quiet (position: 1).

Outputs

vector (a pathlike object or string representing an existing file) – The output image of the major eigenvectors of the diffusion tensor image.

Threshold

Link to code

Bases: CommandLine

Wrapped executable: threshold.

Create bitwise image by thresholding image intensity.

By default, the threshold level is determined using a histogram analysis to cut out the background. Otherwise, the threshold intensity can be specified using command line options. Note that only the first study is used for thresholding.

Example

>>> import nipype.interfaces.mrtrix as mrt
>>> thresh = mrt.Threshold()
>>> thresh.inputs.in_file = 'wm_mask.mif'
>>> thresh.run()
Mandatory Inputs

in_file (a pathlike object or string representing an existing file) – The input image to be thresholded. Maps to a command-line argument: %s (position: -2).

Optional Inputs

  • absolute_threshold_value (a float) – Specify threshold value as absolute intensity. Maps to a command-line argument: -abs %s.

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

  • debug (a boolean) – Display debugging messages. Maps to a command-line argument: -debug (position: 1).

  • 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: {})

  • invert (a boolean) – Invert output binary mask. Maps to a command-line argument: -invert (position: 1).

  • out_filename (a pathlike object or string representing a file) – The output binary image mask. Maps to a command-line argument: %s (position: -1).

  • percentage_threshold_value (a float) – Specify threshold value as a percentage of the peak intensity in the input image. Maps to a command-line argument: -percent %s.

  • quiet (a boolean) – Do not display information messages or progress status. Maps to a command-line argument: -quiet (position: 1).

  • replace_zeros_with_NaN (a boolean) – Replace all zero values with NaN. Maps to a command-line argument: -nan (position: 1).

Outputs

out_file (a pathlike object or string representing an existing file) – The output binary image mask.