[–seed_density int] [–step_size float] [–tracking_method str] [–pmf_threshold float] [–max_angle float] [–out_dir str] [–out_tractogram str] [–save_seeds] pam_files stopping_files seeding_files
Workflow for Local Fiber Tracking.
This workflow use a saved peaks and metrics (PAM) file as input.
pam_files Path to the peaks and metrics files. This path may contain wildcards to use multiple masks at once. stopping_files Path to images (e.g. FA) used for stopping criterion for tracking. seeding_files A binary image showing where we need to seed for tracking.
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If True, uses a binary stopping criterion. If the provided stopping_files are not binary, stopping_thr will be used to binarize the images.
Threshold applied to stopping volume’s data to identify where tracking has to stop (default 0.2).
Number of seeds per dimension inside voxel (default 1). For example, seed_density of 2 means 8 regularly distributed points in the voxel. And seed density of 1 means 1 point at the center of the voxel.
Step size used for tracking (default 0.5mm).
Select direction getter strategy : - “eudx” (Uses the peaks saved in the pam_files) - “deterministic” or “det” for a deterministic tracking (Uses the sh saved in the pam_files, default) - “probabilistic” or “prob” for a Probabilistic tracking (Uses the sh saved in the pam_files) - “closestpeaks” or “cp” for a ClosestPeaks tracking (Uses the sh saved in the pam_files)
Threshold for ODF functions (default 0.1).
Maximum angle between streamline segments (range [0, 90], default 30).
If true, save the seeds associated to their streamline in the ‘data_per_streamline’ Tractogram dictionary using ‘seeds’ as the key.
Output directory (default input file directory).
Name of the tractogram file to be saved (default ‘tractogram.trk’).
References: Garyfallidis, University of Cambridge, PhD thesis 2012.Amirbekian, University of California San Francisco, PhD thesis 2017. Garyfallidis, E., M. Brett, B. Amirbekian, A. Rokem, S. Van Der Walt, M. Descoteaux, and I. Nimmo-Smith. Dipy, a library for the analysis of diffusion MRI data. Frontiers in Neuroinformatics, 1-18, 2014.