usage: __main__.py [-h] [--mask MASK] [--mask_wm MASK_WM]
[--fa_thresh FA_THRESH] [--min_fa_thresh MIN_FA_THRESH]
[--min_nvox MIN_NVOX]
[--roi_radii ROI_RADII [ROI_RADII ...]]
[--roi_center tuple(3) tuple(3) tuple(3)]
[--b0_threshold thr] [--skip_b0_check]
[--precision PRECISION] [-v [{DEBUG,INFO,WARNING}]] [-f]
in_dwi in_bval in_bvec frf_file
Compute a single Fiber Response Function from a DWI.
A DTI fit is made, and voxels containing a single fiber population are
found using a threshold on the FA.
Formerly: scil_compute_ssst_frf.py
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Reference:
[1] Tournier et al. NeuroImage 2007
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positional arguments:
in_dwi Path of the input diffusion volume.
in_bval Path of the bvals file, in FSL format.
in_bvec Path of the bvecs file, in FSL format.
frf_file Path to the output FRF file, in .txt format, saved by Numpy.
options:
-h, --help show this help message and exit
--mask MASK Path to a binary mask. Only the data inside the mask will be used
for computations and reconstruction. Useful if no white matter mask
is available.
--mask_wm MASK_WM Path to a binary white matter mask. Only the data inside this mask
and above the threshold defined by --fa_thresh will be used to estimate the
fiber response function.
--fa_thresh FA_THRESH
If supplied, use this threshold as the initial threshold to select
single fiber voxels. [0.7]
--min_fa_thresh MIN_FA_THRESH
If supplied, this is the minimal value that will be tried when looking
for single fiber voxels. [0.5]
--min_nvox MIN_NVOX Minimal number of voxels needing to be identified as single fiber voxels
in the automatic estimation. [300]
--roi_radii ROI_RADII [ROI_RADII ...]
If supplied, use those radii to select a cuboid roi to estimate the
response functions. The roi will be a cuboid spanning from the middle of
the volume in each direction with the different radii. The type is either
an int (e.g. --roi_radii 10) or an array-like (3,) (e.g. --roi_radii 20 30 10). [[20]]
--roi_center tuple(3) tuple(3) tuple(3)
If supplied, use this center to span the roi of size roi_radius. [center of the 3D volume]
--b0_threshold thr Threshold under which b-values are considered to be b0s.
[Default: 20]
* Note. We would expect to find at least one b-value in the
range [0, b0_threshold]. To skip this check, use --skip_b0_check.
--skip_b0_check By default, we supervise that at least one b0 exists in your data
(i.e. b-values below the default --b0_threshold). Use this option to
allow continuing even if the minimum b-value is suspiciously high.
If no b-value is found below the threshold, the script will continue
with your minimal b-value as new --b0_threshold.
Use with care, and only if you understand your data.
--precision PRECISION
Precision for floating point values. Numbers are rounded up to
the number of decimals provided. [Default: 12]
-v [{DEBUG,INFO,WARNING}]
Produces verbose output depending on the provided level.
Default level is warning, default when using -v is info.
-f Force overwriting of the output files.
Scilpy version: 2.0.2