usage: __main__.py [-h] [--mask MASK] [--mask_wm MASK_WM] [--mask_gm MASK_GM]
[--mask_csf MASK_CSF] [--fa_thr_wm FA_THR_WM]
[--fa_thr_gm FA_THR_GM] [--fa_thr_csf FA_THR_CSF]
[--md_thr_gm MD_THR_GM] [--md_thr_csf MD_THR_CSF]
[--min_nvox MIN_NVOX] [--tolerance TOLERANCE]
[--skip_b0_check] [--dti_bval_limit DTI_BVAL_LIMIT]
[--roi_radii ROI_RADII [ROI_RADII ...]]
[--roi_center tuple(3) tuple(3) tuple(3)]
[--wm_frf_mask file] [--gm_frf_mask file]
[--csf_frf_mask file] [--precision PRECISION]
[-v [{DEBUG,INFO,WARNING}]] [-f]
in_dwi in_bval in_bvec out_wm_frf out_gm_frf out_csf_frf
Compute response functions for multi-shell multi-tissue (MSMT) constrained
spherical deconvolution from DWI data.
The script computes a response function for white-matter (wm),
gray-matter (gm), csf and the mean b=0.
- In the wm, we compute the response function in each voxel where the FA is
superior at threshold_fa_wm.
- In the gm (or csf), we compute the response function in each voxel where
the FA is below at threshold_fa_gm (or threshold_fa_csf) and where the MD
is below threshold_md_gm (or threshold_md_csf).
We output one response function file for each tissue, containing the response
function for each b-value (arranged by lines). These are saved as the diagonal
of the axis-symmetric diffusion tensor (3 e-values) and a mean b0 value.
For example, a typical wm_frf is [15e-4, 4e-4, 4e-4, 700], where the tensor
e-values are (15,4,4)x10^-4 mm^2/s and the mean b0 is 700.
Based on B. Jeurissen et al., Multi-tissue constrained spherical deconvolution
for improved analysis of multi-shell diffusion MRI data. Neuroimage (2014)
Formerly: scil_compute_msmt_frf.py
positional arguments:
in_dwi Path to the input diffusion volume.
in_bval Path to the bval file, in FSL format.
in_bvec Path to the bvec file, in FSL format.
out_wm_frf Path to the output WM frf file, in .txt format.
out_gm_frf Path to the output GM frf file, in .txt format.
out_csf_frf Path to the output CSF frf file, in .txt format.
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 tissue masks are available.
--mask_wm MASK_WM Path to the input WM mask file, used to improve the final WM frf mask.
--mask_gm MASK_GM Path to the input GM mask file, used to improve the final GM frf mask.
--mask_csf MASK_CSF Path to the input CSF mask file, used to improve the final CSF frf mask.
--fa_thr_wm FA_THR_WM
If supplied, use this threshold to select single WM fiber voxels from the FA inside the WM mask defined by mask_wm. Each voxel above this threshold will be selected. [0.7]
--fa_thr_gm FA_THR_GM
If supplied, use this threshold to select GM voxels from the FA inside the GM mask defined by mask_gm. Each voxel below this threshold will be selected. [0.2]
--fa_thr_csf FA_THR_CSF
If supplied, use this threshold to select CSF voxels from the FA inside the CSF mask defined by mask_csf. Each voxel below this threshold will be selected. [0.1]
--md_thr_gm MD_THR_GM
If supplied, use this threshold to select GM voxels from the MD inside the GM mask defined by mask_gm. Each voxel below this threshold will be selected. [0.0007]
--md_thr_csf MD_THR_CSF
If supplied, use this threshold to select CSF voxels from the MD inside the CSF mask defined by mask_csf. Each voxel below this threshold will be selected. [0.003]
--min_nvox MIN_NVOX Minimal number of voxels needed for each tissue masks in order to proceed to frf estimation. [100]
--tolerance TOLERANCE
The tolerated gap between the b-values to extract and the current b-value. [20]
--skip_b0_check By default, we supervise that at least one b0 exists in your data
(i.e. b-values below the default --tolerance). 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 the original --tolerance and no b0 volumes.
Use with care, and only if you understand your data.
--dti_bval_limit DTI_BVAL_LIMIT
The highest b-value taken for the DTI model. [1200]
--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 cuboid roi using roi_radii. [center of the 3D volume] (e.g. --roi_center 66 79 79)
--wm_frf_mask file Path to the output WM frf mask file, the voxels used to compute the WM frf.
--gm_frf_mask file Path to the output GM frf mask file, the voxels used to compute the GM frf.
--csf_frf_mask file Path to the output CSF frf mask file, the voxels used to compute the CSF frf.
--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