nipype.interfaces.mrtrix.tensors module¶
ConstrainedSphericalDeconvolution¶
Bases: CommandLine
Wrapped executable:
csdeconv
.Perform non-negativity constrained spherical deconvolution.
Note that this program makes use of implied symmetries in the diffusion profile. First, the fact the signal attenuation profile is real implies that it has conjugate symmetry, i.e. Y(l,-m) = Y(l,m)* (where * denotes the complex conjugate). Second, the diffusion profile should be antipodally symmetric (i.e. S(x) = S(-x)), implying that all odd l components should be zero. Therefore, this program only computes the even elements. Note that the spherical harmonics equations used here differ slightly from those conventionally used, in that the (-1)^m factor has been omitted. This should be taken into account in all subsequent calculations. Each volume in the output image corresponds to a different spherical harmonic component, according to the following convention:
[0] Y(0,0)
[1] Im {Y(2,2)}
[2] Im {Y(2,1)}
[3] Y(2,0)
[4] Re {Y(2,1)}
[5] Re {Y(2,2)}
[6] Im {Y(4,4)}
[7] Im {Y(4,3)}
Example
>>> import nipype.interfaces.mrtrix as mrt >>> csdeconv = mrt.ConstrainedSphericalDeconvolution() >>> csdeconv.inputs.in_file = 'dwi.mif' >>> csdeconv.inputs.encoding_file = 'encoding.txt' >>> csdeconv.run()
- in_filea pathlike object or string representing an existing file
Diffusion-weighted image. Maps to a command-line argument:
%s
(position: -3).- response_filea pathlike object or string representing an existing file
The diffusion-weighted signal response function for a single fibre population (see EstimateResponse). Maps to a command-line argument:
%s
(position: -2).
- argsa string
Additional parameters to the command. Maps to a command-line argument:
%s
.- debuga boolean
Display debugging messages. Maps to a command-line argument:
-debug
.- directions_filea pathlike object or string representing an existing file
A text file containing the [ el az ] pairs for the directions: Specify the directions over which to apply the non-negativity constraint (by default, the built-in 300 direction set is used). Maps to a command-line argument:
-directions %s
(position: -2).- encoding_filea 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).- 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:
{}
)- filter_filea pathlike object or string representing an existing file
A text file containing the filtering coefficients for each even harmonic order.the linear frequency filtering parameters used for the initial linear spherical deconvolution step (default = [ 1 1 1 0 0 ]). Maps to a command-line argument:
-filter %s
(position: -2).- iterationsan integer
The maximum number of iterations to perform for each voxel (default = 50). Maps to a command-line argument:
-niter %s
.- lambda_valuea float
The regularisation parameter lambda that controls the strength of the constraint (default = 1.0). Maps to a command-line argument:
-lambda %s
.- mask_imagea pathlike object or string representing an existing file
Only perform computation within the specified binary brain mask image. Maps to a command-line argument:
-mask %s
(position: 2).- maximum_harmonic_orderan integer
Set the maximum harmonic order for the output series. By default, the program will use the highest possible lmax given the number of diffusion-weighted images. Maps to a command-line argument:
-lmax %s
.- normalisea boolean
Normalise the DW signal to the b=0 image. Maps to a command-line argument:
-normalise
(position: 3).- out_filenamea pathlike object or string representing a file
Output filename. Maps to a command-line argument:
%s
(position: -1).- threshold_valuea float
The threshold below which the amplitude of the FOD is assumed to be zero, expressed as a fraction of the mean value of the initial FOD (default = 0.1). Maps to a command-line argument:
-threshold %s
.
- spherical_harmonics_imagea pathlike object or string representing an existing file
Spherical harmonics image.
DWI2SphericalHarmonicsImage¶
Bases: CommandLine
Wrapped executable:
dwi2SH
.Convert base diffusion-weighted images to their spherical harmonic representation.
This program outputs the spherical harmonic decomposition for the set measured signal attenuations. The signal attenuations are calculated by identifying the b-zero images from the diffusion encoding supplied (i.e. those with zero as the b-value), and dividing the remaining signals by the mean b-zero signal intensity. The spherical harmonic decomposition is then calculated by least-squares linear fitting. Note that this program makes use of implied symmetries in the diffusion profile.
First, the fact the signal attenuation profile is real implies that it has conjugate symmetry, i.e. Y(l,-m) = Y(l,m)* (where * denotes the complex conjugate). Second, the diffusion profile should be antipodally symmetric (i.e. S(x) = S(-x)), implying that all odd l components should be zero. Therefore, this program only computes the even elements.
Note that the spherical harmonics equations used here differ slightly from those conventionally used, in that the (-1)^m factor has been omitted. This should be taken into account in all subsequent calculations.
Each volume in the output image corresponds to a different spherical harmonic component, according to the following convention:
[0] Y(0,0)
[1] Im {Y(2,2)}
[2] Im {Y(2,1)}
[3] Y(2,0)
[4] Re {Y(2,1)}
[5] Re {Y(2,2)}
[6] Im {Y(4,4)}
[7] Im {Y(4,3)}
Example
>>> import nipype.interfaces.mrtrix as mrt >>> dwi2SH = mrt.DWI2SphericalHarmonicsImage() >>> dwi2SH.inputs.in_file = 'diffusion.nii' >>> dwi2SH.inputs.encoding_file = 'encoding.txt' >>> dwi2SH.run()
- encoding_filea 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_filea pathlike object or string representing an existing file
Diffusion-weighted images. 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:
{}
)- maximum_harmonic_ordera float
Set the maximum harmonic order for the output series. By default, the program will use the highest possible lmax given the number of diffusion-weighted images. Maps to a command-line argument:
-lmax %s
.- normalisea boolean
Normalise the DW signal to the b=0 image. Maps to a command-line argument:
-normalise
(position: 3).- out_filenamea pathlike object or string representing a file
Output filename. Maps to a command-line argument:
%s
(position: -1).
- spherical_harmonics_imagea pathlike object or string representing an existing file
Spherical harmonics image.
Directions2Amplitude¶
Bases: CommandLine
Wrapped executable:
dir2amp
.convert directions image to amplitudes
Example
>>> import nipype.interfaces.mrtrix as mrt >>> amplitudes = mrt.Directions2Amplitude() >>> amplitudes.inputs.in_file = 'peak_directions.mif' >>> amplitudes.run()
- in_filea pathlike object or string representing an existing file
The input directions image. Each volume corresponds to the x, y & z component of each direction vector in turn. Maps to a command-line argument:
%s
(position: -2).
- argsa string
Additional parameters to the command. Maps to a command-line argument:
%s
.- display_debuga boolean
Display debugging messages. Maps to a command-line argument:
-debug
.- display_infoa boolean
Display information messages. Maps to a command-line argument:
-info
.- 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_peaksan integer
The number of peaks to extract (default is 3). Maps to a command-line argument:
-num %s
.- out_filea pathlike object or string representing a file
The output amplitudes image. Maps to a command-line argument:
%s
(position: -1).- peak_directionsa list of from 2 to 2 items which are a float
Phi theta. the direction of a peak to estimate. The algorithm will attempt to find the same number of peaks as have been specified using this option phi: the azimuthal angle of the direction (in degrees). theta: the elevation angle of the direction (in degrees, from the vertical z-axis). Maps to a command-line argument:
-direction %s
.- peaks_imagea pathlike object or string representing an existing file
The program will try to find the peaks that most closely match those in the image provided. Maps to a command-line argument:
-peaks %s
.- quiet_displaya boolean
Do not display information messages or progress status. Maps to a command-line argument:
-quiet
.
- out_filea pathlike object or string representing an existing file
Amplitudes image.
EstimateResponseForSH¶
Bases: CommandLine
Wrapped executable:
estimate_response
.Estimates the fibre response function for use in spherical deconvolution.
Example
>>> import nipype.interfaces.mrtrix as mrt >>> estresp = mrt.EstimateResponseForSH() >>> estresp.inputs.in_file = 'dwi.mif' >>> estresp.inputs.mask_image = 'dwi_WMProb.mif' >>> estresp.inputs.encoding_file = 'encoding.txt' >>> estresp.run()
- encoding_filea 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_filea pathlike object or string representing an existing file
Diffusion-weighted images. Maps to a command-line argument:
%s
(position: -3).- mask_imagea pathlike object or string representing an existing file
Only perform computation within the specified binary brain mask image. Maps to a command-line argument:
%s
(position: -2).
- argsa string
Additional parameters to the command. Maps to a command-line argument:
%s
.- debuga boolean
Display debugging messages. Maps to a command-line argument:
-debug
.- 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:
{}
)- maximum_harmonic_orderan integer
Set the maximum harmonic order for the output series. By default, the program will use the highest possible lmax given the number of diffusion-weighted images. Maps to a command-line argument:
-lmax %s
.- normalisea boolean
Normalise the DW signal to the b=0 image. Maps to a command-line argument:
-normalise
.- out_filenamea pathlike object or string representing a file
Output filename. Maps to a command-line argument:
%s
(position: -1).- quieta boolean
Do not display information messages or progress status. Maps to a command-line argument:
-quiet
.
- responsea pathlike object or string representing an existing file
Spherical harmonics image.
FSL2MRTrix¶
Bases: BaseInterface
Converts separate b-values and b-vectors from text files (FSL style) into a 4xN text file in which 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).
Example
>>> import nipype.interfaces.mrtrix as mrt >>> fsl2mrtrix = mrt.FSL2MRTrix() >>> fsl2mrtrix.inputs.bvec_file = 'bvecs' >>> fsl2mrtrix.inputs.bval_file = 'bvals' >>> fsl2mrtrix.inputs.invert_y = True >>> fsl2mrtrix.run()
- bval_filea pathlike object or string representing an existing file
FSL b-values file (1xN text file).
- bvec_filea pathlike object or string representing an existing file
FSL b-vectors file (3xN text file).
- invert_xa boolean
Inverts the b-vectors along the x-axis. (Nipype default value:
False
)- invert_ya boolean
Inverts the b-vectors along the y-axis. (Nipype default value:
False
)- invert_za boolean
Inverts the b-vectors along the z-axis. (Nipype default value:
False
)- out_encoding_filea pathlike object or string representing a file
Output encoding filename.
- encoding_filea pathlike object or string representing a file
The 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 gradientand b gives the b-value in units (1000 s/mm^2).
FindShPeaks¶
Bases: CommandLine
Wrapped executable:
find_SH_peaks
.identify the orientations of the N largest peaks of a SH profile
Example
>>> import nipype.interfaces.mrtrix as mrt >>> shpeaks = mrt.FindShPeaks() >>> shpeaks.inputs.in_file = 'csd.mif' >>> shpeaks.inputs.directions_file = 'dirs.txt' >>> shpeaks.inputs.num_peaks = 2 >>> shpeaks.run()
- directions_filea pathlike object or string representing an existing file
The set of directions to use as seeds for the peak finding. Maps to a command-line argument:
%s
(position: -2).- in_filea pathlike object or string representing an existing file
The input image of SH coefficients. Maps to a command-line argument:
%s
(position: -3).
- argsa string
Additional parameters to the command. Maps to a command-line argument:
%s
.- display_debuga boolean
Display debugging messages. Maps to a command-line argument:
-debug
.- display_infoa boolean
Display information messages. Maps to a command-line argument:
-info
.- 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_peaksan integer
The number of peaks to extract (default is 3). Maps to a command-line argument:
-num %s
.- out_filea pathlike object or string representing a file
The output image. Each volume corresponds to the x, y & z component of each peak direction vector in turn. Maps to a command-line argument:
%s
(position: -1).- peak_directionsa list of from 2 to 2 items which are a float
Phi theta. the direction of a peak to estimate. The algorithm will attempt to find the same number of peaks as have been specified using this option phi: the azimuthal angle of the direction (in degrees). theta: the elevation angle of the direction (in degrees, from the vertical z-axis). Maps to a command-line argument:
-direction %s
.- peak_thresholda float
Only peak amplitudes greater than the threshold will be considered. Maps to a command-line argument:
-threshold %s
.- peaks_imagea pathlike object or string representing an existing file
The program will try to find the peaks that most closely match those in the image provided. Maps to a command-line argument:
-peaks %s
.- quiet_displaya boolean
Do not display information messages or progress status. Maps to a command-line argument:
-quiet
.
- out_filea pathlike object or string representing an existing file
Peak directions image.
GenerateDirections¶
Bases: CommandLine
Wrapped executable:
gendir
.generate a set of directions evenly distributed over a hemisphere.
Example
>>> import nipype.interfaces.mrtrix as mrt >>> gendir = mrt.GenerateDirections() >>> gendir.inputs.num_dirs = 300 >>> gendir.run()
- num_dirsan integer
The number of directions to generate. Maps to a command-line argument:
%s
(position: -2).
- argsa string
Additional parameters to the command. Maps to a command-line argument:
%s
.- display_debuga boolean
Display debugging messages. Maps to a command-line argument:
-debug
.- display_infoa boolean
Display information messages. Maps to a command-line argument:
-info
.- 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:
{}
)- niteran integer
Specify the maximum number of iterations to perform. Maps to a command-line argument:
-niter %s
.- out_filea pathlike object or string representing a file
The text file to write the directions to, as [ az el ] pairs. Maps to a command-line argument:
%s
(position: -1).- powera float
Specify exponent to use for repulsion power law. Maps to a command-line argument:
-power %s
.- quiet_displaya boolean
Do not display information messages or progress status. Maps to a command-line argument:
-quiet
.
- out_filea pathlike object or string representing an existing file
Directions file.
- nipype.interfaces.mrtrix.tensors.concat_files(bvec_file, bval_file, invert_x, invert_y, invert_z)¶