interfaces.mrtrix.preprocess

DWI2Tensor

Link to code

Wraps command 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()                                   

Inputs:

[Mandatory]
in_file: (a list of items which are an existing file name)
        Diffusion-weighted images
        flag: %s, position: -2

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
debug: (a boolean)
        Display debugging messages.
        flag: -debug, position: 1
encoding_file: (a file name)
        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()
        flag: -grad %s, position: 2
environ: (a dictionary with keys which are a newbytes or None or a
         newstr or None and with values which are a newbytes or None or a
         newstr or None, nipype default value: {})
        Environment variables
ignore_exception: (a boolean, nipype default value: False)
        Print an error message instead of throwing an exception in case the
        interface fails to run
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.
        flag: -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.
        flag: -ignorevolumes %s, position: 2
out_filename: (a file name)
        Output tensor filename
        flag: %s, position: -1
quiet: (a boolean)
        Do not display information messages or progress status.
        flag: -quiet, position: 1
terminal_output: (u'stream' or u'allatonce' or u'file' or u'none')
        Control terminal output: `stream` - displays to terminal immediately
        (default), `allatonce` - waits till command is finished to display
        output, `file` - writes output to file, `none` - output is ignored

Outputs:

tensor: (an existing file name)
        path/name of output diffusion tensor image

Erode

Link to code

Wraps command 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()                                     

Inputs:

[Mandatory]
in_file: (an existing file name)
        Input mask image to be eroded
        flag: %s, position: -2

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
debug: (a boolean)
        Display debugging messages.
        flag: -debug, position: 1
dilate: (a boolean)
        Perform dilation rather than erosion
        flag: -dilate, position: 1
environ: (a dictionary with keys which are a newbytes or None or a
         newstr or None and with values which are a newbytes or None or a
         newstr or None, nipype default value: {})
        Environment variables
ignore_exception: (a boolean, nipype default value: False)
        Print an error message instead of throwing an exception in case the
        interface fails to run
number_of_passes: (an integer (int or long))
        the number of passes (default: 1)
        flag: -npass %s
out_filename: (a file name)
        Output image filename
        flag: %s, position: -1
quiet: (a boolean)
        Do not display information messages or progress status.
        flag: -quiet, position: 1
terminal_output: (u'stream' or u'allatonce' or u'file' or u'none')
        Control terminal output: `stream` - displays to terminal immediately
        (default), `allatonce` - waits till command is finished to display
        output, `file` - writes output to file, `none` - output is ignored

Outputs:

out_file: (an existing file name)
        the output image

GenerateWhiteMatterMask

Link to code

Wraps command 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()                                     

Inputs:

[Mandatory]
binary_mask: (an existing file name)
        Binary brain mask
        flag: %s, position: -2
encoding_file: (an existing file name)
        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
        flag: -grad %s, position: 1
in_file: (an existing file name)
        Diffusion-weighted images
        flag: %s, position: -3

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
environ: (a dictionary with keys which are a newbytes or None or a
         newstr or None and with values which are a newbytes or None or a
         newstr or None, nipype default value: {})
        Environment variables
ignore_exception: (a boolean, nipype default value: False)
        Print an error message instead of throwing an exception in case the
        interface fails to run
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)
        flag: -margin %s
out_WMProb_filename: (a file name)
        Output WM probability image filename
        flag: %s, position: -1
terminal_output: (u'stream' or u'allatonce' or u'file' or u'none')
        Control terminal output: `stream` - displays to terminal immediately
        (default), `allatonce` - waits till command is finished to display
        output, `file` - writes output to file, `none` - output is ignored

Outputs:

WMprobabilitymap: (an existing file name)
        WMprobabilitymap

MRConvert

Link to code

Wraps command 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()                                 

Inputs:

[Mandatory]
in_file: (an existing file name)
        voxel-order data filename
        flag: %s, position: -2

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
environ: (a dictionary with keys which are a newbytes or None or a
         newstr or None and with values which are a newbytes or None or a
         newstr or None, nipype default value: {})
        Environment variables
extension: (u'mif' or u'nii' or u'float' or u'char' or u'short' or
         u'int' or u'long' or u'double', nipype default value: mif)
        "i.e. Bfloat". Can be "char", "short", "int", "long", "float" or
        "double"
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.
        flag: -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.
        flag: %s, position: 2
ignore_exception: (a boolean, nipype default value: False)
        Print an error message instead of throwing an exception in case the
        interface fails to run
layout: (u'nii' or u'float' or u'char' or u'short' or u'int' or
         u'long' or u'double')
        specify the layout of the data in memory. The actual layout produced
        will depend on whether the output image format can support it.
        flag: -output %s, position: 2
offset_bias: (a float)
        Apply offset to the intensity values.
        flag: -scale %d, position: 3
out_filename: (a file name)
        Output filename
        flag: %s, position: -1
output_datatype: (u'nii' or u'float' or u'char' or u'short' or u'int'
         or u'long' or u'double')
        "i.e. Bfloat". Can be "char", "short", "int", "long", "float" or
        "double"
        flag: -output %s, position: 2
prs: (a boolean)
        Assume that the DW gradients are specified in the PRS frame (Siemens
        DICOM only).
        flag: -prs, position: 3
replace_NaN_with_zero: (a boolean)
        Replace all NaN values with zero.
        flag: -zero, position: 3
resample: (a float)
        Apply scaling to the intensity values.
        flag: -scale %d, position: 3
terminal_output: (u'stream' or u'allatonce' or u'file' or u'none')
        Control terminal output: `stream` - displays to terminal immediately
        (default), `allatonce` - waits till command is finished to display
        output, `file` - writes output to file, `none` - output is ignored
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.
        flag: -vox %s, position: 3

Outputs:

converted: (an existing file name)
        path/name of 4D volume in voxel order

MRMultiply

Link to code

Wraps command 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()                                             

Inputs:

[Mandatory]
in_files: (a list of items which are an existing file name)
        Input images to be multiplied
        flag: %s, position: -2

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
debug: (a boolean)
        Display debugging messages.
        flag: -debug, position: 1
environ: (a dictionary with keys which are a newbytes or None or a
         newstr or None and with values which are a newbytes or None or a
         newstr or None, nipype default value: {})
        Environment variables
ignore_exception: (a boolean, nipype default value: False)
        Print an error message instead of throwing an exception in case the
        interface fails to run
out_filename: (a file name)
        Output image filename
        flag: %s, position: -1
quiet: (a boolean)
        Do not display information messages or progress status.
        flag: -quiet, position: 1
terminal_output: (u'stream' or u'allatonce' or u'file' or u'none')
        Control terminal output: `stream` - displays to terminal immediately
        (default), `allatonce` - waits till command is finished to display
        output, `file` - writes output to file, `none` - output is ignored

Outputs:

out_file: (an existing file name)
        the output image of the multiplication

MRTransform

Link to code

Wraps command mrtransform

Apply spatial transformations or reslice images

Example

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

Inputs:

[Mandatory]
in_files: (a list of items which are an existing file name)
        Input images to be transformed
        flag: %s, position: -2

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
debug: (a boolean)
        Display debugging messages.
        flag: -debug, position: 1
environ: (a dictionary with keys which are a newbytes or None or a
         newstr or None and with values which are a newbytes or None or a
         newstr or None, nipype default value: {})
        Environment variables
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.
        flag: -flipx, position: 1
ignore_exception: (a boolean, nipype default value: False)
        Print an error message instead of throwing an exception in case the
        interface fails to run
invert: (a boolean)
        Invert the specified transform before using it
        flag: -inverse, position: 1
out_filename: (a file name)
        Output image
        flag: %s, position: -1
quiet: (a boolean)
        Do not display information messages or progress status.
        flag: -quiet, position: 1
reference_image: (an existing file name)
        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.
        flag: -reference %s, position: 1
replace_transform: (a boolean)
        replace the current transform by that specified, rather than
        applying it to the current transform
        flag: -replace, position: 1
template_image: (an existing file name)
        Reslice the input image to match the specified template image.
        flag: -template %s, position: 1
terminal_output: (u'stream' or u'allatonce' or u'file' or u'none')
        Control terminal output: `stream` - displays to terminal immediately
        (default), `allatonce` - waits till command is finished to display
        output, `file` - writes output to file, `none` - output is ignored
transformation_file: (an existing file name)
        The transform to apply, in the form of a 4x4 ascii file.
        flag: -transform %s, position: 1

Outputs:

out_file: (an existing file name)
        the output image of the transformation

MRTrixViewer

Link to code

Wraps command 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()                                    

Inputs:

[Mandatory]
in_files: (a list of items which are an existing file name)
        Input images to be viewed
        flag: %s, position: -2

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
debug: (a boolean)
        Display debugging messages.
        flag: -debug, position: 1
environ: (a dictionary with keys which are a newbytes or None or a
         newstr or None and with values which are a newbytes or None or a
         newstr or None, nipype default value: {})
        Environment variables
ignore_exception: (a boolean, nipype default value: False)
        Print an error message instead of throwing an exception in case the
        interface fails to run
quiet: (a boolean)
        Do not display information messages or progress status.
        flag: -quiet, position: 1
terminal_output: (u'stream' or u'allatonce' or u'file' or u'none')
        Control terminal output: `stream` - displays to terminal immediately
        (default), `allatonce` - waits till command is finished to display
        output, `file` - writes output to file, `none` - output is ignored

Outputs:

None

MedianFilter3D

Link to code

Wraps command 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()                                  

Inputs:

[Mandatory]
in_file: (an existing file name)
        Input images to be smoothed
        flag: %s, position: -2

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
debug: (a boolean)
        Display debugging messages.
        flag: -debug, position: 1
environ: (a dictionary with keys which are a newbytes or None or a
         newstr or None and with values which are a newbytes or None or a
         newstr or None, nipype default value: {})
        Environment variables
ignore_exception: (a boolean, nipype default value: False)
        Print an error message instead of throwing an exception in case the
        interface fails to run
out_filename: (a file name)
        Output image filename
        flag: %s, position: -1
quiet: (a boolean)
        Do not display information messages or progress status.
        flag: -quiet, position: 1
terminal_output: (u'stream' or u'allatonce' or u'file' or u'none')
        Control terminal output: `stream` - displays to terminal immediately
        (default), `allatonce` - waits till command is finished to display
        output, `file` - writes output to file, `none` - output is ignored

Outputs:

out_file: (an existing file name)
        the output image

Tensor2ApparentDiffusion

Link to code

Wraps command 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()                                

Inputs:

[Mandatory]
in_file: (an existing file name)
        Diffusion tensor image
        flag: %s, position: -2

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
debug: (a boolean)
        Display debugging messages.
        flag: -debug, position: 1
environ: (a dictionary with keys which are a newbytes or None or a
         newstr or None and with values which are a newbytes or None or a
         newstr or None, nipype default value: {})
        Environment variables
ignore_exception: (a boolean, nipype default value: False)
        Print an error message instead of throwing an exception in case the
        interface fails to run
out_filename: (a file name)
        Output Fractional Anisotropy filename
        flag: %s, position: -1
quiet: (a boolean)
        Do not display information messages or progress status.
        flag: -quiet, position: 1
terminal_output: (u'stream' or u'allatonce' or u'file' or u'none')
        Control terminal output: `stream` - displays to terminal immediately
        (default), `allatonce` - waits till command is finished to display
        output, `file` - writes output to file, `none` - output is ignored

Outputs:

ADC: (an existing file name)
        the output image of the major eigenvectors of the diffusion tensor
        image.

Tensor2FractionalAnisotropy

Link to code

Wraps command 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()                                 

Inputs:

[Mandatory]
in_file: (an existing file name)
        Diffusion tensor image
        flag: %s, position: -2

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
debug: (a boolean)
        Display debugging messages.
        flag: -debug, position: 1
environ: (a dictionary with keys which are a newbytes or None or a
         newstr or None and with values which are a newbytes or None or a
         newstr or None, nipype default value: {})
        Environment variables
ignore_exception: (a boolean, nipype default value: False)
        Print an error message instead of throwing an exception in case the
        interface fails to run
out_filename: (a file name)
        Output Fractional Anisotropy filename
        flag: %s, position: -1
quiet: (a boolean)
        Do not display information messages or progress status.
        flag: -quiet, position: 1
terminal_output: (u'stream' or u'allatonce' or u'file' or u'none')
        Control terminal output: `stream` - displays to terminal immediately
        (default), `allatonce` - waits till command is finished to display
        output, `file` - writes output to file, `none` - output is ignored

Outputs:

FA: (an existing file name)
        the output image of the major eigenvectors of the diffusion tensor
        image.

Tensor2Vector

Link to code

Wraps command 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()                             

Inputs:

[Mandatory]
in_file: (an existing file name)
        Diffusion tensor image
        flag: %s, position: -2

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
debug: (a boolean)
        Display debugging messages.
        flag: -debug, position: 1
environ: (a dictionary with keys which are a newbytes or None or a
         newstr or None and with values which are a newbytes or None or a
         newstr or None, nipype default value: {})
        Environment variables
ignore_exception: (a boolean, nipype default value: False)
        Print an error message instead of throwing an exception in case the
        interface fails to run
out_filename: (a file name)
        Output vector filename
        flag: %s, position: -1
quiet: (a boolean)
        Do not display information messages or progress status.
        flag: -quiet, position: 1
terminal_output: (u'stream' or u'allatonce' or u'file' or u'none')
        Control terminal output: `stream` - displays to terminal immediately
        (default), `allatonce` - waits till command is finished to display
        output, `file` - writes output to file, `none` - output is ignored

Outputs:

vector: (an existing file name)
        the output image of the major eigenvectors of the diffusion tensor
        image.

Threshold

Link to code

Wraps command 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()                                             

Inputs:

[Mandatory]
in_file: (an existing file name)
        The input image to be thresholded
        flag: %s, position: -2

[Optional]
absolute_threshold_value: (a float)
        Specify threshold value as absolute intensity.
        flag: -abs %s
args: (a unicode string)
        Additional parameters to the command
        flag: %s
debug: (a boolean)
        Display debugging messages.
        flag: -debug, position: 1
environ: (a dictionary with keys which are a newbytes or None or a
         newstr or None and with values which are a newbytes or None or a
         newstr or None, nipype default value: {})
        Environment variables
ignore_exception: (a boolean, nipype default value: False)
        Print an error message instead of throwing an exception in case the
        interface fails to run
invert: (a boolean)
        Invert output binary mask
        flag: -invert, position: 1
out_filename: (a file name)
        The output binary image mask.
        flag: %s, position: -1
percentage_threshold_value: (a float)
        Specify threshold value as a percentage of the peak intensity in the
        input image.
        flag: -percent %s
quiet: (a boolean)
        Do not display information messages or progress status.
        flag: -quiet, position: 1
replace_zeros_with_NaN: (a boolean)
        Replace all zero values with NaN
        flag: -nan, position: 1
terminal_output: (u'stream' or u'allatonce' or u'file' or u'none')
        Control terminal output: `stream` - displays to terminal immediately
        (default), `allatonce` - waits till command is finished to display
        output, `file` - writes output to file, `none` - output is ignored

Outputs:

out_file: (an existing file name)
        The output binary image mask.