[Mandatory]
in_file: (an existing file name)
input file to be processed
flag: %s, position: -2
out_file: (a file name, nipype default value: tracked.tck)
output file containing tracks
flag: %s, position: -1
[Optional]
act_file: (an existing file name)
use the Anatomically-Constrained Tractography framework during
tracking; provided image must be in the 5TT (five - tissue - type)
format
flag: -act %s
algorithm: ('iFOD2' or 'FACT' or 'iFOD1' or 'Nulldist' or 'SD_Stream'
or 'Tensor_Det' or 'Tensor_Prob', nipype default value: iFOD2)
tractography algorithm to be used
flag: -algorithm %s
angle: (a float)
set the maximum angle between successive steps (default is 90deg x
stepsize / voxelsize)
flag: -angle %f
args: (a string)
Additional parameters to the command
flag: %s
backtrack: (a boolean)
allow tracks to be truncated
flag: -backtrack
bval_scale: ('yes' or 'no')
specifies whether the b - values should be scaled by the square of
the corresponding DW gradient norm, as often required for multishell
or DSI DW acquisition schemes. The default action can also be set in
the MRtrix config file, under the BValueScaling entry. Valid choices
are yes / no, true / false, 0 / 1 (default: true).
flag: -bvalue_scaling %s
crop_at_gmwmi: (a boolean)
crop streamline endpoints more precisely as they cross the GM-WM
interface
flag: -crop_at_gmwmi
cutoff: (a float)
set the FA or FOD amplitude cutoff for terminating tracks (default
is 0.1)
flag: -cutoff %f
cutoff_init: (a float)
set the minimum FA or FOD amplitude for initiating tracks (default
is the same as the normal cutoff)
flag: -initcutoff %f
downsample: (a float)
downsample the generated streamlines to reduce output file size
flag: -downsample %f
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
grad_file: (an existing file name)
dw gradient scheme (MRTrix format
flag: -grad %s
grad_fsl: (a tuple of the form: (an existing file name, an existing
file name))
(bvecs, bvals) dw gradient scheme (FSL format
flag: -fslgrad %s %s
ignore_exception: (a boolean, nipype default value: False)
Print an error message instead of throwing an exception in case the
interface fails to run
in_bval: (an existing file name)
bvals file in FSL format
in_bvec: (an existing file name)
bvecs file in FSL format
flag: -fslgrad %s %s
init_dir: (a tuple of the form: (a float, a float, a float))
specify an initial direction for the tracking (this should be
supplied as a vector of 3 comma-separated values
flag: -initdirection %f,%f,%f
max_length: (a float)
set the maximum length of any track in mm (default is 100 x
voxelsize)
flag: -maxlength %f
max_seed_attempts: (an integer (int or long))
set the maximum number of times that the tracking algorithm should
attempt to find an appropriate tracking direction from a given seed
point
flag: -max_seed_attempts %d
max_tracks: (an integer (int or long))
set 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
min_length: (a float)
set the minimum length of any track in mm (default is 5 x voxelsize)
flag: -minlength %f
n_samples: (an integer (int or long))
set the number of FOD samples to take per step for the 2nd order
(iFOD2) method
flag: -samples %d
n_tracks: (an integer (int or long))
set 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
flag: -number %d
n_trials: (an integer (int or long))
set the maximum number of sampling trials at each point (only used
for probabilistic tracking)
flag: -trials %d
noprecompt: (a boolean)
do NOT pre-compute legendre polynomial values. Warning: this will
slow down the algorithm by a factor of approximately 4
flag: -noprecomputed
nthreads: (an integer (int or long))
number of threads. if zero, the number of available cpus will be
used
flag: -nthreads %d
out_seeds: (a file name)
output the seed location of all successful streamlines to a file
flag: -output_seeds %s
power: (an integer (int or long))
raise the FOD to the power specified (default is 1/nsamples)
flag: -power %d
roi_excl: (an existing file name or a tuple of the form: (a float, a
float, a float, a float))
specify an exclusion region of interest, streamlines that enter ANY
exclude region will be discarded
flag: -exclude %s
roi_incl: (an existing file name or a tuple of the form: (a float, a
float, a float, a float))
specify an inclusion region of interest, streamlines must traverse
ALL inclusion regions to be accepted
flag: -include %s
roi_mask: (an existing file name or a tuple of the form: (a float, a
float, a float, a float))
specify a masking region of interest. If defined,streamlines exiting
the mask will be truncated
flag: -mask %s
seed_dynamic: (an existing file name)
determine seed points dynamically using the SIFT model (must not
provide any other seeding mechanism). Note that while this seeding
mechanism improves the distribution of reconstructed streamlines
density, it should NOT be used as a substitute for the SIFT method
itself.
flag: -seed_dynamic %s
seed_gmwmi: (an existing file name)
seed from the grey matter - white matter interface (only valid if
using ACT framework)
flag: -seed_gmwmi %s
requires: act_file
seed_grid_voxel: (a tuple of the form: (an existing file name, an
integer (int or long)))
seed a fixed number of streamlines per voxel in a mask image; place
seeds on a 3D mesh grid (grid_size argument is per axis; so a
grid_size of 3 results in 27 seeds per voxel)
flag: -seed_grid_per_voxel %s %d
mutually_exclusive: seed_image, seed_rnd_voxel
seed_image: (an existing file name)
seed streamlines entirely at random within mask
flag: -seed_image %s
seed_rejection: (an existing file name)
seed from an image using rejection sampling (higher values = more
probable to seed from
flag: -seed_rejection %s
seed_rnd_voxel: (a tuple of the form: (an existing file name, an
integer (int or long)))
seed a fixed number of streamlines per voxel in a mask image; random
placement of seeds in each voxel
flag: -seed_random_per_voxel %s %d
mutually_exclusive: seed_image, seed_grid_voxel
seed_sphere: (a tuple of the form: (a float, a float, a float, a
float))
spherical seed
flag: -seed_sphere %f,%f,%f,%f
sph_trait: (a tuple of the form: (a float, a float, a float, a
float))
flag: %f,%f,%f,%f
step_size: (a float)
set the step size of the algorithm in mm (default is 0.1 x
voxelsize; for iFOD2: 0.5 x voxelsize)
flag: -step %f
stop: (a boolean)
stop propagating a streamline once it has traversed all 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
use_rk4: (a boolean)
use 4th-order Runge-Kutta integration (slower, but eliminates
curvature overshoot in 1st-order deterministic methods)
flag: -rk4
