======================== dipy_slr ======================== usage: dipy_slr [-h] [--x0 str] [--rm_small_clusters int] [--qbx_thr [int [int ...]]] [--num_threads int] [--greater_than int] [--less_than int] [--nb_pts int] [--progressive] [--out_dir str] [--out_moved str] [--out_affine str] [--out_stat_centroids str] [--out_moving_centroids str] [--out_moved_centroids str] static_files moving_files Streamline-based linear registration. For efficiency we apply the registration on cluster centroids and remove small clusters. positional arguments: static_files moving_files optional arguments: -h, --help show this help message and exit --x0 str rigid, similarity or affine transformation model (default affine) --rm_small_clusters int Remove clusters that have less than `rm_small_clusters` (default 50) --qbx_thr [int [int ...]] Thresholds for QuickBundlesX (default [40, 30, 20, 15]) --num_threads int Number of threads. If None (default) then all available threads will be used. Only metrics using OpenMP will use this variable. --greater_than int Keep streamlines that have length greater than this value (default 50) --less_than int Keep streamlines have length less than this value (default 250) --nb_pts int Number of points for discretizing each streamline (default 20) --progressive (default True) output arguments(optional): --out_dir str Output directory (default input file directory) --out_moved str Filename of moved tractogram (default 'moved.trk') --out_affine str Filename of affine for SLR transformation (default 'affine.txt') --out_stat_centroids str Filename of static centroids (default 'static_centroids.trk') --out_moving_centroids str Filename of moving centroids (default 'moving_centroids.trk') --out_moved_centroids str Filename of moved centroids (default 'moved_centroids.trk') References: .. [Garyfallidis15] Garyfallidis et al. "Robust and efficient linearregistration of white-matter fascicles in the space ofstreamlines", NeuroImage, 117, 124--140, 2015 .. [Garyfallidis14] Garyfallidis et al., "Direct native-space fiberbundle alignment for group comparisons", ISMRM, 2014. .. [Garyfallidis17] Garyfallidis et al. Recognition of white matterbundles using local and global streamline-based registrationand clustering, NeuroImage, 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.