interfaces.mrtrix.tracking¶
DiffusionTensorStreamlineTrack¶
Wraps the executable command streamtrack
.
Specialized interface to StreamlineTrack. This interface is used for streamline tracking from diffusion tensor data, and calls the MRtrix function ‘streamtrack’ with the option ‘DT_STREAM’
Example¶
>>> import nipype.interfaces.mrtrix as mrt
>>> dtstrack = mrt.DiffusionTensorStreamlineTrack()
>>> dtstrack.inputs.in_file = 'data.Bfloat'
>>> dtstrack.inputs.seed_file = 'seed_mask.nii'
>>> dtstrack.run()
Inputs:
[Mandatory]
in_file: (an existing file name)
the image containing the source data.The type of data required
depends on the type of tracking as set in the preceeding argument.
For DT methods, the base DWI are needed. For SD methods, the SH
harmonic coefficients of the FOD are needed.
argument: ``%s``, position: -2
gradient_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
argument: ``-grad %s``, position: -2
[Optional]
include_spec: (a list of from 4 to 4 items which are a float)
inclusion specification in mm and radius (x y z r)
argument: ``-include %s``, position: 2
mutually_exclusive: include_file, include_spec
initial_direction: (a list of from 2 to 2 items which are an integer
(int or long))
Specify the initial tracking direction as a vector
argument: ``-initdirection %s``
no_mask_interpolation: (a boolean)
Turns off trilinear interpolation of mask images.
argument: ``-nomaskinterp``
stop: (a boolean)
stop track as soon as it enters any of the include regions.
argument: ``-stop``
mask_file: (an existing file name)
mask file. Only tracks within mask.
argument: ``-mask %s``
mutually_exclusive: mask_file, mask_spec
inputmodel: ('DT_STREAM' or 'SD_PROB' or 'SD_STREAM', nipype default
value: DT_STREAM)
input model type
argument: ``%s``, position: -3
step_size: (a float)
Set the step size of the algorithm in mm (default is 0.2).
argument: ``-step %s``
unidirectional: (a boolean)
Track from the seed point in one direction only (default is to track
in both directions).
argument: ``-unidirectional``
exclude_spec: (a list of from 4 to 4 items which are a float)
exclusion specification in mm and radius (x y z r)
argument: ``-exclude %s``, position: 2
mutually_exclusive: exclude_file, exclude_spec
exclude_file: (an existing file name)
exclusion file
argument: ``-exclude %s``
mutually_exclusive: exclude_file, exclude_spec
minimum_radius_of_curvature: (a float)
Set the minimum radius of curvature (default is 2 mm for DT_STREAM,
0 for SD_STREAM, 1 mm for SD_PROB and DT_PROB)
argument: ``-curvature %s``
initial_cutoff_value: (a float)
Sets the minimum FA or FOD amplitude for initiating tracks (default
is twice the normal cutoff).
argument: ``-initcutoff %s``
seed_file: (an existing file name)
seed file
argument: ``-seed %s``
mutually_exclusive: seed_file, seed_spec
out_file: (a file name)
output data file
argument: ``%s``, position: -1
maximum_tract_length: (a float)
Sets the maximum length of any track in millimeters (default is 200
mm).
argument: ``-length %s``
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
mask_spec: (a list of from 4 to 4 items which are a float)
Mask specification in mm and radius (x y z r). Tracks will be
terminated when they leave the ROI.
argument: ``-mask %s``, position: 2
mutually_exclusive: mask_file, mask_spec
maximum_number_of_tracks: (an integer (int or long))
Sets the maximum number of tracks to generate.The program will not
generate more tracks than this number, even if the desired number of
tracks hasn't yet been reached(default is 100 x number).
argument: ``-maxnum %d``
desired_number_of_tracks: (an integer (int or long))
Sets the desired number of tracks.The program will continue to
generate tracks until this number of tracks have been selected and
written to the output file(default is 100 for *_STREAM methods, 1000
for *_PROB methods).
argument: ``-number %d``
do_not_precompute: (a boolean)
Turns off precomputation of the legendre polynomial values. Warning:
this will slow down the algorithm by a factor of approximately 4.
argument: ``-noprecomputed``
include_file: (an existing file name)
inclusion file
argument: ``-include %s``
mutually_exclusive: include_file, include_spec
cutoff_value: (a float)
Set the FA or FOD amplitude cutoff for terminating tracks (default
is 0.1).
argument: ``-cutoff %s``
minimum_tract_length: (a float)
Sets the minimum length of any track in millimeters (default is 10
mm).
argument: ``-minlength %s``
seed_spec: (a list of from 4 to 4 items which are a float)
seed specification in mm and radius (x y z r)
argument: ``-seed %s``, position: 2
mutually_exclusive: seed_file, seed_spec
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', nipype default value: {})
Environment variables
Outputs:
tracked: (an existing file name)
output file containing reconstructed tracts
FilterTracks¶
Wraps the executable command filter_tracks
.
Use regions-of-interest to select a subset of tracks from a given MRtrix track file.
Example¶
>>> import nipype.interfaces.mrtrix as mrt
>>> filt = mrt.FilterTracks()
>>> filt.inputs.in_file = 'tracks.tck'
>>> filt.run()
Inputs:
[Mandatory]
in_file: (an existing file name)
input tracks to be filtered
argument: ``%s``, position: -2
[Optional]
invert: (a boolean)
invert the matching process, so that tracks that wouldotherwise have
been included are now excluded and vice-versa.
argument: ``-invert``
include_spec: (a list of from 4 to 4 items which are a float)
inclusion specification in mm and radius (x y z r)
argument: ``-include %s``, position: 2
mutually_exclusive: include_file, include_spec
out_file: (a file name)
Output filtered track filename
argument: ``%s``, position: -1
no_mask_interpolation: (a boolean)
Turns off trilinear interpolation of mask images.
argument: ``-nomaskinterp``
include_file: (an existing file name)
inclusion file
argument: ``-include %s``
mutually_exclusive: include_file, include_spec
minimum_tract_length: (a float)
Sets the minimum length of any track in millimeters (default is 10
mm).
argument: ``-minlength %s``
debug: (a boolean)
Display debugging messages.
argument: ``-debug``, position: 1
exclude_spec: (a list of from 4 to 4 items which are a float)
exclusion specification in mm and radius (x y z r)
argument: ``-exclude %s``, position: 2
mutually_exclusive: exclude_file, exclude_spec
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', nipype default value: {})
Environment variables
exclude_file: (an existing file name)
exclusion file
argument: ``-exclude %s``
mutually_exclusive: exclude_file, exclude_spec
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
quiet: (a boolean)
Do not display information messages or progress status.
argument: ``-quiet``, position: 1
Outputs:
out_file: (an existing file name)
the output filtered tracks
ProbabilisticSphericallyDeconvolutedStreamlineTrack¶
Wraps the executable command streamtrack
.
Performs probabilistic tracking using spherically deconvolved data
Specialized interface to StreamlineTrack. This interface is used for probabilistic tracking from spherically deconvolved data, and calls the MRtrix function ‘streamtrack’ with the option ‘SD_PROB’
Example¶
>>> import nipype.interfaces.mrtrix as mrt
>>> sdprobtrack = mrt.ProbabilisticSphericallyDeconvolutedStreamlineTrack()
>>> sdprobtrack.inputs.in_file = 'data.Bfloat'
>>> sdprobtrack.inputs.seed_file = 'seed_mask.nii'
>>> sdprobtrack.run()
Inputs:
[Mandatory]
in_file: (an existing file name)
the image containing the source data.The type of data required
depends on the type of tracking as set in the preceeding argument.
For DT methods, the base DWI are needed. For SD methods, the SH
harmonic coefficients of the FOD are needed.
argument: ``%s``, position: -2
[Optional]
include_spec: (a list of from 4 to 4 items which are a float)
inclusion specification in mm and radius (x y z r)
argument: ``-include %s``, position: 2
mutually_exclusive: include_file, include_spec
initial_direction: (a list of from 2 to 2 items which are an integer
(int or long))
Specify the initial tracking direction as a vector
argument: ``-initdirection %s``
no_mask_interpolation: (a boolean)
Turns off trilinear interpolation of mask images.
argument: ``-nomaskinterp``
stop: (a boolean)
stop track as soon as it enters any of the include regions.
argument: ``-stop``
mask_file: (an existing file name)
mask file. Only tracks within mask.
argument: ``-mask %s``
mutually_exclusive: mask_file, mask_spec
inputmodel: ('DT_STREAM' or 'SD_PROB' or 'SD_STREAM', nipype default
value: DT_STREAM)
input model type
argument: ``%s``, position: -3
step_size: (a float)
Set the step size of the algorithm in mm (default is 0.2).
argument: ``-step %s``
unidirectional: (a boolean)
Track from the seed point in one direction only (default is to track
in both directions).
argument: ``-unidirectional``
exclude_spec: (a list of from 4 to 4 items which are a float)
exclusion specification in mm and radius (x y z r)
argument: ``-exclude %s``, position: 2
mutually_exclusive: exclude_file, exclude_spec
exclude_file: (an existing file name)
exclusion file
argument: ``-exclude %s``
mutually_exclusive: exclude_file, exclude_spec
minimum_radius_of_curvature: (a float)
Set the minimum radius of curvature (default is 2 mm for DT_STREAM,
0 for SD_STREAM, 1 mm for SD_PROB and DT_PROB)
argument: ``-curvature %s``
initial_cutoff_value: (a float)
Sets the minimum FA or FOD amplitude for initiating tracks (default
is twice the normal cutoff).
argument: ``-initcutoff %s``
seed_file: (an existing file name)
seed file
argument: ``-seed %s``
mutually_exclusive: seed_file, seed_spec
out_file: (a file name)
output data file
argument: ``%s``, position: -1
maximum_tract_length: (a float)
Sets the maximum length of any track in millimeters (default is 200
mm).
argument: ``-length %s``
mask_spec: (a list of from 4 to 4 items which are a float)
Mask specification in mm and radius (x y z r). Tracks will be
terminated when they leave the ROI.
argument: ``-mask %s``, position: 2
mutually_exclusive: mask_file, mask_spec
maximum_number_of_tracks: (an integer (int or long))
Sets the maximum number of tracks to generate.The program will not
generate more tracks than this number, even if the desired number of
tracks hasn't yet been reached(default is 100 x number).
argument: ``-maxnum %d``
desired_number_of_tracks: (an integer (int or long))
Sets the desired number of tracks.The program will continue to
generate tracks until this number of tracks have been selected and
written to the output file(default is 100 for *_STREAM methods, 1000
for *_PROB methods).
argument: ``-number %d``
do_not_precompute: (a boolean)
Turns off precomputation of the legendre polynomial values. Warning:
this will slow down the algorithm by a factor of approximately 4.
argument: ``-noprecomputed``
include_file: (an existing file name)
inclusion file
argument: ``-include %s``
mutually_exclusive: include_file, include_spec
cutoff_value: (a float)
Set the FA or FOD amplitude cutoff for terminating tracks (default
is 0.1).
argument: ``-cutoff %s``
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
minimum_tract_length: (a float)
Sets the minimum length of any track in millimeters (default is 10
mm).
argument: ``-minlength %s``
seed_spec: (a list of from 4 to 4 items which are a float)
seed specification in mm and radius (x y z r)
argument: ``-seed %s``, position: 2
mutually_exclusive: seed_file, seed_spec
maximum_number_of_trials: (an integer (int or long))
Set the maximum number of sampling trials at each point (only used
for probabilistic tracking).
argument: ``-trials %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', nipype default value: {})
Environment variables
Outputs:
tracked: (an existing file name)
output file containing reconstructed tracts
SphericallyDeconvolutedStreamlineTrack¶
Wraps the executable command streamtrack
.
Performs streamline tracking using spherically deconvolved data
Specialized interface to StreamlineTrack. This interface is used for streamline tracking from spherically deconvolved data, and calls the MRtrix function ‘streamtrack’ with the option ‘SD_STREAM’
Example¶
>>> import nipype.interfaces.mrtrix as mrt
>>> sdtrack = mrt.SphericallyDeconvolutedStreamlineTrack()
>>> sdtrack.inputs.in_file = 'data.Bfloat'
>>> sdtrack.inputs.seed_file = 'seed_mask.nii'
>>> sdtrack.run()
Inputs:
[Mandatory]
in_file: (an existing file name)
the image containing the source data.The type of data required
depends on the type of tracking as set in the preceeding argument.
For DT methods, the base DWI are needed. For SD methods, the SH
harmonic coefficients of the FOD are needed.
argument: ``%s``, position: -2
[Optional]
include_spec: (a list of from 4 to 4 items which are a float)
inclusion specification in mm and radius (x y z r)
argument: ``-include %s``, position: 2
mutually_exclusive: include_file, include_spec
initial_direction: (a list of from 2 to 2 items which are an integer
(int or long))
Specify the initial tracking direction as a vector
argument: ``-initdirection %s``
no_mask_interpolation: (a boolean)
Turns off trilinear interpolation of mask images.
argument: ``-nomaskinterp``
stop: (a boolean)
stop track as soon as it enters any of the include regions.
argument: ``-stop``
mask_file: (an existing file name)
mask file. Only tracks within mask.
argument: ``-mask %s``
mutually_exclusive: mask_file, mask_spec
inputmodel: ('DT_STREAM' or 'SD_PROB' or 'SD_STREAM', nipype default
value: DT_STREAM)
input model type
argument: ``%s``, position: -3
step_size: (a float)
Set the step size of the algorithm in mm (default is 0.2).
argument: ``-step %s``
unidirectional: (a boolean)
Track from the seed point in one direction only (default is to track
in both directions).
argument: ``-unidirectional``
exclude_file: (an existing file name)
exclusion file
argument: ``-exclude %s``
mutually_exclusive: exclude_file, exclude_spec
minimum_radius_of_curvature: (a float)
Set the minimum radius of curvature (default is 2 mm for DT_STREAM,
0 for SD_STREAM, 1 mm for SD_PROB and DT_PROB)
argument: ``-curvature %s``
initial_cutoff_value: (a float)
Sets the minimum FA or FOD amplitude for initiating tracks (default
is twice the normal cutoff).
argument: ``-initcutoff %s``
seed_file: (an existing file name)
seed file
argument: ``-seed %s``
mutually_exclusive: seed_file, seed_spec
out_file: (a file name)
output data file
argument: ``%s``, position: -1
maximum_tract_length: (a float)
Sets the maximum length of any track in millimeters (default is 200
mm).
argument: ``-length %s``
mask_spec: (a list of from 4 to 4 items which are a float)
Mask specification in mm and radius (x y z r). Tracks will be
terminated when they leave the ROI.
argument: ``-mask %s``, position: 2
mutually_exclusive: mask_file, mask_spec
maximum_number_of_tracks: (an integer (int or long))
Sets the maximum number of tracks to generate.The program will not
generate more tracks than this number, even if the desired number of
tracks hasn't yet been reached(default is 100 x number).
argument: ``-maxnum %d``
desired_number_of_tracks: (an integer (int or long))
Sets the desired number of tracks.The program will continue to
generate tracks until this number of tracks have been selected and
written to the output file(default is 100 for *_STREAM methods, 1000
for *_PROB methods).
argument: ``-number %d``
do_not_precompute: (a boolean)
Turns off precomputation of the legendre polynomial values. Warning:
this will slow down the algorithm by a factor of approximately 4.
argument: ``-noprecomputed``
include_file: (an existing file name)
inclusion file
argument: ``-include %s``
mutually_exclusive: include_file, include_spec
cutoff_value: (a float)
Set the FA or FOD amplitude cutoff for terminating tracks (default
is 0.1).
argument: ``-cutoff %s``
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
minimum_tract_length: (a float)
Sets the minimum length of any track in millimeters (default is 10
mm).
argument: ``-minlength %s``
seed_spec: (a list of from 4 to 4 items which are a float)
seed specification in mm and radius (x y z r)
argument: ``-seed %s``, position: 2
mutually_exclusive: seed_file, seed_spec
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', nipype default value: {})
Environment variables
exclude_spec: (a list of from 4 to 4 items which are a float)
exclusion specification in mm and radius (x y z r)
argument: ``-exclude %s``, position: 2
mutually_exclusive: exclude_file, exclude_spec
Outputs:
tracked: (an existing file name)
output file containing reconstructed tracts
StreamlineTrack¶
Wraps the executable command streamtrack
.
Performs tractography using one of the following models: ‘dt_prob’, ‘dt_stream’, ‘sd_prob’, ‘sd_stream’, Where ‘dt’ stands for diffusion tensor, ‘sd’ stands for spherical deconvolution, and ‘prob’ stands for probabilistic.
Example¶
>>> import nipype.interfaces.mrtrix as mrt
>>> strack = mrt.StreamlineTrack()
>>> strack.inputs.inputmodel = 'SD_PROB'
>>> strack.inputs.in_file = 'data.Bfloat'
>>> strack.inputs.seed_file = 'seed_mask.nii'
>>> strack.inputs.mask_file = 'mask.nii'
>>> strack.cmdline
'streamtrack -mask mask.nii -seed seed_mask.nii SD_PROB data.Bfloat data_tracked.tck'
>>> strack.run()
Inputs:
[Mandatory]
in_file: (an existing file name)
the image containing the source data.The type of data required
depends on the type of tracking as set in the preceeding argument.
For DT methods, the base DWI are needed. For SD methods, the SH
harmonic coefficients of the FOD are needed.
argument: ``%s``, position: -2
[Optional]
include_spec: (a list of from 4 to 4 items which are a float)
inclusion specification in mm and radius (x y z r)
argument: ``-include %s``, position: 2
mutually_exclusive: include_file, include_spec
initial_direction: (a list of from 2 to 2 items which are an integer
(int or long))
Specify the initial tracking direction as a vector
argument: ``-initdirection %s``
no_mask_interpolation: (a boolean)
Turns off trilinear interpolation of mask images.
argument: ``-nomaskinterp``
stop: (a boolean)
stop track as soon as it enters any of the include regions.
argument: ``-stop``
mask_file: (an existing file name)
mask file. Only tracks within mask.
argument: ``-mask %s``
mutually_exclusive: mask_file, mask_spec
inputmodel: ('DT_STREAM' or 'SD_PROB' or 'SD_STREAM', nipype default
value: DT_STREAM)
input model type
argument: ``%s``, position: -3
step_size: (a float)
Set the step size of the algorithm in mm (default is 0.2).
argument: ``-step %s``
unidirectional: (a boolean)
Track from the seed point in one direction only (default is to track
in both directions).
argument: ``-unidirectional``
exclude_file: (an existing file name)
exclusion file
argument: ``-exclude %s``
mutually_exclusive: exclude_file, exclude_spec
minimum_radius_of_curvature: (a float)
Set the minimum radius of curvature (default is 2 mm for DT_STREAM,
0 for SD_STREAM, 1 mm for SD_PROB and DT_PROB)
argument: ``-curvature %s``
initial_cutoff_value: (a float)
Sets the minimum FA or FOD amplitude for initiating tracks (default
is twice the normal cutoff).
argument: ``-initcutoff %s``
seed_file: (an existing file name)
seed file
argument: ``-seed %s``
mutually_exclusive: seed_file, seed_spec
out_file: (a file name)
output data file
argument: ``%s``, position: -1
maximum_tract_length: (a float)
Sets the maximum length of any track in millimeters (default is 200
mm).
argument: ``-length %s``
mask_spec: (a list of from 4 to 4 items which are a float)
Mask specification in mm and radius (x y z r). Tracks will be
terminated when they leave the ROI.
argument: ``-mask %s``, position: 2
mutually_exclusive: mask_file, mask_spec
maximum_number_of_tracks: (an integer (int or long))
Sets the maximum number of tracks to generate.The program will not
generate more tracks than this number, even if the desired number of
tracks hasn't yet been reached(default is 100 x number).
argument: ``-maxnum %d``
desired_number_of_tracks: (an integer (int or long))
Sets the desired number of tracks.The program will continue to
generate tracks until this number of tracks have been selected and
written to the output file(default is 100 for *_STREAM methods, 1000
for *_PROB methods).
argument: ``-number %d``
do_not_precompute: (a boolean)
Turns off precomputation of the legendre polynomial values. Warning:
this will slow down the algorithm by a factor of approximately 4.
argument: ``-noprecomputed``
include_file: (an existing file name)
inclusion file
argument: ``-include %s``
mutually_exclusive: include_file, include_spec
cutoff_value: (a float)
Set the FA or FOD amplitude cutoff for terminating tracks (default
is 0.1).
argument: ``-cutoff %s``
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
minimum_tract_length: (a float)
Sets the minimum length of any track in millimeters (default is 10
mm).
argument: ``-minlength %s``
seed_spec: (a list of from 4 to 4 items which are a float)
seed specification in mm and radius (x y z r)
argument: ``-seed %s``, position: 2
mutually_exclusive: seed_file, seed_spec
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', nipype default value: {})
Environment variables
exclude_spec: (a list of from 4 to 4 items which are a float)
exclusion specification in mm and radius (x y z r)
argument: ``-exclude %s``, position: 2
mutually_exclusive: exclude_file, exclude_spec
Outputs:
tracked: (an existing file name)
output file containing reconstructed tracts
Tracks2Prob¶
Wraps the executable command tracks2prob
.
Convert a tract file into a map of the fraction of tracks to enter each voxel - also known as a tract density image (TDI) - in MRtrix’s image format (.mif). This can be viewed using MRview or converted to Nifti using MRconvert.
Example¶
>>> import nipype.interfaces.mrtrix as mrt
>>> tdi = mrt.Tracks2Prob()
>>> tdi.inputs.in_file = 'dwi_CSD_tracked.tck'
>>> tdi.inputs.colour = True
>>> tdi.run()
Inputs:
[Mandatory]
in_file: (an existing file name)
tract file
argument: ``%s``, position: -2
[Optional]
fraction: (a boolean)
produce an image of the fraction of fibres through each voxel (as a
proportion of the total number in the file), rather than the count.
argument: ``-fraction``, position: 3
colour: (a boolean)
add colour to the output image according to the direction of the
tracks.
argument: ``-colour``, 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.
argument: ``-vox %s``, position: 2
out_filename: (a file name)
output data file
argument: ``%s``, position: -1
resample: (a float)
resample the tracks at regular intervals using Hermite
interpolation. If omitted, the program will select an appropriate
interpolation factor automatically.
argument: ``-resample %d``, position: 3
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', nipype default value: {})
Environment variables
output_datatype: ('Bit' or 'Int8' or 'UInt8' or 'Int16' or 'UInt16'
or 'Int32' or 'UInt32' or 'float32' or 'float64')
"i.e. Bfloat". Can be "char", "short", "int", "long", "float" or
"double"
argument: ``-datatype %s``, position: 2
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
template_file: (an existing file name)
an image file to be used as a template for the output (the output
image wil have the same transform and field of view)
argument: ``-template %s``, position: 1
Outputs:
tract_image: (an existing file name)
Output tract count or track density image