usage: __main__.py [-h] [--max_lobes MAX_LOBES] [--at AT] [--rt RT]
[--min_sep_angle MIN_SEP_ANGLE]
[--max_fit_angle MAX_FIT_ANGLE] [--mask MASK]
[-v [{DEBUG,INFO,WARNING}]] [--processes NBR] [-f]
in_sh out_bingham
Script for fitting a Bingham distribution to each fODF lobe, as described
in [1].
The Bingham fit is saved, with each Bingham distribution described by 7
coefficients (for example, for a maximum number of lobes of 5, the number
of coefficients is 7 x 5 = 35 -- less than the number of coefficients for
SH of maximum order 8).
Using 12 threads, the execution takes approximately 30 minutes for a brain with
1mm isotropic resolution.
Formerly: scil_fit_bingham_to_fodf.py
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References:
[1] T. W. Riffert, J. Schreiber, A. Anwander, and T. R. Knösche, “Beyond
fractional anisotropy: Extraction of bundle-specific structural metrics
from crossing fiber models,” NeuroImage, vol. 100, pp. 176-191, Oct. 2014,
doi: 10.1016/j.neuroimage.2014.06.015.
[2] J. Schreiber, T. Riffert, A. Anwander, and T. R. Knösche, “Plausibility
Tracking: A method to evaluate anatomical connectivity and microstructural
properties along fiber pathways,” NeuroImage, vol. 90, pp. 163-178, Apr.
2014, doi: 10.1016/j.neuroimage.2014.01.002.
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positional arguments:
in_sh Input SH image.
out_bingham Output Bingham functions image.
options:
-h, --help show this help message and exit
--max_lobes MAX_LOBES
Maximum number of lobes per voxel to extract. [5]
--at AT Absolute threshold for peaks extraction. [0.0]
--rt RT Relative threshold for peaks extraction. [0.1]
--min_sep_angle MIN_SEP_ANGLE
Minimum separation angle between two peaks. [25.0]
--max_fit_angle MAX_FIT_ANGLE
Maximum distance in degrees around a peak direction for fitting the Bingham function. [15.0]
--mask MASK Optional mask file. Only SH inside the mask are fitted.
-v [{DEBUG,INFO,WARNING}]
Produces verbose output depending on the provided level.
Default level is warning, default when using -v is info.
--processes NBR Number of sub-processes to start.
Default: [1]
-f Force overwriting of the output files.
Scilpy version: 2.0.2