interfaces.mrtrix.tracking¶
DiffusionTensorStreamlineTrack¶
Wraps 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]
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
flag: -grad %s, position: -2
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.
flag: %s, position: -2
[Optional]
args: (a string)
Additional parameters to the command
flag: %s
cutoff_value: (a float)
Set the FA or FOD amplitude cutoff for terminating tracks (default
is 0.1).
flag: -cutoff %s
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).
flag: -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.
flag: -noprecomputed
environ: (a dictionary with keys which are a value of type 'str' and
with values which are a value of type 'str', nipype default value:
{})
Environment variables
exclude_file: (an existing file name)
exclusion file
flag: -exclude %s
mutually_exclusive: exclude_file, exclude_spec
exclude_spec: (a list of from 4 to 4 items which are a float)
exclusion specification in mm and radius (x y z r)
flag: -exclude %s, position: 2
mutually_exclusive: exclude_file, exclude_spec
ignore_exception: (a boolean, nipype default value: False)
Print an error message instead of throwing an exception in case the
interface fails to run
include_file: (an existing file name)
inclusion file
flag: -include %s
mutually_exclusive: include_file, include_spec
include_spec: (a list of from 4 to 4 items which are a float)
inclusion specification in mm and radius (x y z r)
flag: -include %s, position: 2
mutually_exclusive: include_file, include_spec
initial_cutoff_value: (a float)
Sets the minimum FA or FOD amplitude for initiating tracks (default
is twice the normal cutoff).
flag: -initcutoff %s
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
flag: -initdirection %s
inputmodel: ('DT_STREAM' or 'SD_PROB' or 'SD_STREAM', nipype default
value: DT_STREAM)
input model type
flag: %s, position: -3
mask_file: (an existing file name)
mask file. Only tracks within mask.
flag: -mask %s
mutually_exclusive: mask_file, mask_spec
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.
flag: -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).
flag: -maxnum %d
maximum_tract_length: (a float)
Sets the maximum length of any track in millimeters (default is 200
mm).
flag: -length %s
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)
flag: -curvature %s
minimum_tract_length: (a float)
Sets the minimum length of any track in millimeters (default is 10
mm).
flag: -minlength %s
no_mask_interpolation: (a boolean)
Turns off trilinear interpolation of mask images.
flag: -nomaskinterp
out_file: (a file name)
output data file
flag: %s, position: -1
seed_file: (an existing file name)
seed file
flag: -seed %s
mutually_exclusive: seed_file, seed_spec
seed_spec: (a list of from 4 to 4 items which are a float)
seed specification in mm and radius (x y z r)
flag: -seed %s, position: 2
mutually_exclusive: seed_file, seed_spec
step_size: (a float)
Set the step size of the algorithm in mm (default is 0.2).
flag: -step %s
stop: (a boolean)
stop track as soon as it enters any of the include regions.
flag: -stop
terminal_output: ('stream' or 'allatonce' or 'file' or '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
unidirectional: (a boolean)
Track from the seed point in one direction only (default is to track
in both directions).
flag: -unidirectional
Outputs:
tracked: (an existing file name)
output file containing reconstructed tracts
FilterTracks¶
Wraps 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
flag: %s, position: -2
[Optional]
args: (a 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 value of type 'str' and
with values which are a value of type 'str', nipype default value:
{})
Environment variables
exclude_file: (an existing file name)
exclusion file
flag: -exclude %s
mutually_exclusive: exclude_file, exclude_spec
exclude_spec: (a list of from 4 to 4 items which are a float)
exclusion specification in mm and radius (x y z r)
flag: -exclude %s, position: 2
mutually_exclusive: exclude_file, exclude_spec
ignore_exception: (a boolean, nipype default value: False)
Print an error message instead of throwing an exception in case the
interface fails to run
include_file: (an existing file name)
inclusion file
flag: -include %s
mutually_exclusive: include_file, include_spec
include_spec: (a list of from 4 to 4 items which are a float)
inclusion specification in mm and radius (x y z r)
flag: -include %s, position: 2
mutually_exclusive: include_file, include_spec
invert: (a boolean)
invert the matching process, so that tracks that wouldotherwise have
been included are now excluded and vice-versa.
flag: -invert
minimum_tract_length: (a float)
Sets the minimum length of any track in millimeters (default is 10
mm).
flag: -minlength %s
no_mask_interpolation: (a boolean)
Turns off trilinear interpolation of mask images.
flag: -nomaskinterp
out_file: (a file name)
Output filtered track filename
flag: %s, position: -1
quiet: (a boolean)
Do not display information messages or progress status.
flag: -quiet, position: 1
terminal_output: ('stream' or 'allatonce' or 'file' or '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 filtered tracks
ProbabilisticSphericallyDeconvolutedStreamlineTrack¶
Wraps 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.
flag: %s, position: -2
[Optional]
args: (a string)
Additional parameters to the command
flag: %s
cutoff_value: (a float)
Set the FA or FOD amplitude cutoff for terminating tracks (default
is 0.1).
flag: -cutoff %s
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).
flag: -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.
flag: -noprecomputed
environ: (a dictionary with keys which are a value of type 'str' and
with values which are a value of type 'str', nipype default value:
{})
Environment variables
exclude_file: (an existing file name)
exclusion file
flag: -exclude %s
mutually_exclusive: exclude_file, exclude_spec
exclude_spec: (a list of from 4 to 4 items which are a float)
exclusion specification in mm and radius (x y z r)
flag: -exclude %s, position: 2
mutually_exclusive: exclude_file, exclude_spec
ignore_exception: (a boolean, nipype default value: False)
Print an error message instead of throwing an exception in case the
interface fails to run
include_file: (an existing file name)
inclusion file
flag: -include %s
mutually_exclusive: include_file, include_spec
include_spec: (a list of from 4 to 4 items which are a float)
inclusion specification in mm and radius (x y z r)
flag: -include %s, position: 2
mutually_exclusive: include_file, include_spec
initial_cutoff_value: (a float)
Sets the minimum FA or FOD amplitude for initiating tracks (default
is twice the normal cutoff).
flag: -initcutoff %s
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
flag: -initdirection %s
inputmodel: ('DT_STREAM' or 'SD_PROB' or 'SD_STREAM', nipype default
value: DT_STREAM)
input model type
flag: %s, position: -3
mask_file: (an existing file name)
mask file. Only tracks within mask.
flag: -mask %s
mutually_exclusive: mask_file, mask_spec
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.
flag: -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).
flag: -maxnum %d
maximum_number_of_trials: (an integer (int or long))
Set the maximum number of sampling trials at each point (only used
for probabilistic tracking).
flag: -trials %s
maximum_tract_length: (a float)
Sets the maximum length of any track in millimeters (default is 200
mm).
flag: -length %s
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)
flag: -curvature %s
minimum_tract_length: (a float)
Sets the minimum length of any track in millimeters (default is 10
mm).
flag: -minlength %s
no_mask_interpolation: (a boolean)
Turns off trilinear interpolation of mask images.
flag: -nomaskinterp
out_file: (a file name)
output data file
flag: %s, position: -1
seed_file: (an existing file name)
seed file
flag: -seed %s
mutually_exclusive: seed_file, seed_spec
seed_spec: (a list of from 4 to 4 items which are a float)
seed specification in mm and radius (x y z r)
flag: -seed %s, position: 2
mutually_exclusive: seed_file, seed_spec
step_size: (a float)
Set the step size of the algorithm in mm (default is 0.2).
flag: -step %s
stop: (a boolean)
stop track as soon as it enters any of the include regions.
flag: -stop
terminal_output: ('stream' or 'allatonce' or 'file' or '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
unidirectional: (a boolean)
Track from the seed point in one direction only (default is to track
in both directions).
flag: -unidirectional
Outputs:
tracked: (an existing file name)
output file containing reconstructed tracts
SphericallyDeconvolutedStreamlineTrack¶
Wraps 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.
flag: %s, position: -2
[Optional]
args: (a string)
Additional parameters to the command
flag: %s
cutoff_value: (a float)
Set the FA or FOD amplitude cutoff for terminating tracks (default
is 0.1).
flag: -cutoff %s
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).
flag: -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.
flag: -noprecomputed
environ: (a dictionary with keys which are a value of type 'str' and
with values which are a value of type 'str', nipype default value:
{})
Environment variables
exclude_file: (an existing file name)
exclusion file
flag: -exclude %s
mutually_exclusive: exclude_file, exclude_spec
exclude_spec: (a list of from 4 to 4 items which are a float)
exclusion specification in mm and radius (x y z r)
flag: -exclude %s, position: 2
mutually_exclusive: exclude_file, exclude_spec
ignore_exception: (a boolean, nipype default value: False)
Print an error message instead of throwing an exception in case the
interface fails to run
include_file: (an existing file name)
inclusion file
flag: -include %s
mutually_exclusive: include_file, include_spec
include_spec: (a list of from 4 to 4 items which are a float)
inclusion specification in mm and radius (x y z r)
flag: -include %s, position: 2
mutually_exclusive: include_file, include_spec
initial_cutoff_value: (a float)
Sets the minimum FA or FOD amplitude for initiating tracks (default
is twice the normal cutoff).
flag: -initcutoff %s
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
flag: -initdirection %s
inputmodel: ('DT_STREAM' or 'SD_PROB' or 'SD_STREAM', nipype default
value: DT_STREAM)
input model type
flag: %s, position: -3
mask_file: (an existing file name)
mask file. Only tracks within mask.
flag: -mask %s
mutually_exclusive: mask_file, mask_spec
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.
flag: -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).
flag: -maxnum %d
maximum_tract_length: (a float)
Sets the maximum length of any track in millimeters (default is 200
mm).
flag: -length %s
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)
flag: -curvature %s
minimum_tract_length: (a float)
Sets the minimum length of any track in millimeters (default is 10
mm).
flag: -minlength %s
no_mask_interpolation: (a boolean)
Turns off trilinear interpolation of mask images.
flag: -nomaskinterp
out_file: (a file name)
output data file
flag: %s, position: -1
seed_file: (an existing file name)
seed file
flag: -seed %s
mutually_exclusive: seed_file, seed_spec
seed_spec: (a list of from 4 to 4 items which are a float)
seed specification in mm and radius (x y z r)
flag: -seed %s, position: 2
mutually_exclusive: seed_file, seed_spec
step_size: (a float)
Set the step size of the algorithm in mm (default is 0.2).
flag: -step %s
stop: (a boolean)
stop track as soon as it enters any of the include regions.
flag: -stop
terminal_output: ('stream' or 'allatonce' or 'file' or '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
unidirectional: (a boolean)
Track from the seed point in one direction only (default is to track
in both directions).
flag: -unidirectional
Outputs:
tracked: (an existing file name)
output file containing reconstructed tracts
StreamlineTrack¶
Wraps 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.
flag: %s, position: -2
[Optional]
args: (a string)
Additional parameters to the command
flag: %s
cutoff_value: (a float)
Set the FA or FOD amplitude cutoff for terminating tracks (default
is 0.1).
flag: -cutoff %s
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).
flag: -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.
flag: -noprecomputed
environ: (a dictionary with keys which are a value of type 'str' and
with values which are a value of type 'str', nipype default value:
{})
Environment variables
exclude_file: (an existing file name)
exclusion file
flag: -exclude %s
mutually_exclusive: exclude_file, exclude_spec
exclude_spec: (a list of from 4 to 4 items which are a float)
exclusion specification in mm and radius (x y z r)
flag: -exclude %s, position: 2
mutually_exclusive: exclude_file, exclude_spec
ignore_exception: (a boolean, nipype default value: False)
Print an error message instead of throwing an exception in case the
interface fails to run
include_file: (an existing file name)
inclusion file
flag: -include %s
mutually_exclusive: include_file, include_spec
include_spec: (a list of from 4 to 4 items which are a float)
inclusion specification in mm and radius (x y z r)
flag: -include %s, position: 2
mutually_exclusive: include_file, include_spec
initial_cutoff_value: (a float)
Sets the minimum FA or FOD amplitude for initiating tracks (default
is twice the normal cutoff).
flag: -initcutoff %s
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
flag: -initdirection %s
inputmodel: ('DT_STREAM' or 'SD_PROB' or 'SD_STREAM', nipype default
value: DT_STREAM)
input model type
flag: %s, position: -3
mask_file: (an existing file name)
mask file. Only tracks within mask.
flag: -mask %s
mutually_exclusive: mask_file, mask_spec
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.
flag: -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).
flag: -maxnum %d
maximum_tract_length: (a float)
Sets the maximum length of any track in millimeters (default is 200
mm).
flag: -length %s
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)
flag: -curvature %s
minimum_tract_length: (a float)
Sets the minimum length of any track in millimeters (default is 10
mm).
flag: -minlength %s
no_mask_interpolation: (a boolean)
Turns off trilinear interpolation of mask images.
flag: -nomaskinterp
out_file: (a file name)
output data file
flag: %s, position: -1
seed_file: (an existing file name)
seed file
flag: -seed %s
mutually_exclusive: seed_file, seed_spec
seed_spec: (a list of from 4 to 4 items which are a float)
seed specification in mm and radius (x y z r)
flag: -seed %s, position: 2
mutually_exclusive: seed_file, seed_spec
step_size: (a float)
Set the step size of the algorithm in mm (default is 0.2).
flag: -step %s
stop: (a boolean)
stop track as soon as it enters any of the include regions.
flag: -stop
terminal_output: ('stream' or 'allatonce' or 'file' or '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
unidirectional: (a boolean)
Track from the seed point in one direction only (default is to track
in both directions).
flag: -unidirectional
Outputs:
tracked: (an existing file name)
output file containing reconstructed tracts
Tracks2Prob¶
Wraps 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
flag: %s, position: -2
[Optional]
args: (a string)
Additional parameters to the command
flag: %s
colour: (a boolean)
add colour to the output image according to the direction of the
tracks.
flag: -colour, position: 3
environ: (a dictionary with keys which are a value of type 'str' and
with values which are a value of type 'str', nipype default value:
{})
Environment variables
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.
flag: -fraction, position: 3
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 data file
flag: %s, position: -1
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"
flag: -datatype %s, position: 2
resample: (a float)
resample the tracks at regular intervals using Hermite
interpolation. If omitted, the program will select an appropriate
interpolation factor automatically.
flag: -resample %d, position: 3
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)
flag: -template %s, position: 1
terminal_output: ('stream' or 'allatonce' or 'file' or '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: 2
Outputs:
tract_image: (an existing file name)
Output tract count or track density image