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()                                   # doctest: +SKIP
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).
args : a unicode 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 (int or long)
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 (int or long)
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).
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()                                     # doctest: +SKIP
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).
args : a unicode 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 (int or long)
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).
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()                                     # doctest: +SKIP
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).
args : a unicode 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).
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()                                 # doctest: +SKIP
in_file : a pathlike object or string representing an existing file
Voxel-order data filename. Maps to a command-line argument: %s (position: -2).
args : a unicode 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).
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()                                             # doctest: +SKIP
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).
args : a unicode 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).
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()                                   # doctest: +SKIP
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).
args : a unicode 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).
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()                                    # doctest: +SKIP
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).
args : a unicode 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()                                    # doctest: +SKIP
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).
args : a unicode 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()                                  # doctest: +SKIP
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).
args : a unicode 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).
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()                                # doctest: +SKIP
in_file : a pathlike object or string representing an existing file
Diffusion tensor image. Maps to a command-line argument: %s (position: -2).
args : a unicode 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).
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()                                 # doctest: +SKIP
in_file : a pathlike object or string representing an existing file
Diffusion tensor image. Maps to a command-line argument: %s (position: -2).
args : a unicode 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).
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()                             # doctest: +SKIP
in_file : a pathlike object or string representing an existing file
Diffusion tensor image. Maps to a command-line argument: %s (position: -2).
args : a unicode 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).
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()                                             # doctest: +SKIP
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).
absolute_threshold_value : a float
Specify threshold value as absolute intensity. Maps to a command-line argument: -abs %s.
args : a unicode 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).
out_file : a pathlike object or string representing an existing file
The output binary image mask.