dipy_slr

Synopsis

Streamline-based linear registration.

For efficiency we apply the registration on cluster centroids and remove small clusters. See [1], [2], [3] for further details.

Usage

dipy_slr [OPTIONS] static_files moving_files

Input Parameters

• static_files

  List of reference/fixed bundle tractograms.

• moving_files

  List of target bundle tractograms that will be moved/registered to match the static bundles.

General Options

• --x0

  rigid, similarity or affine transformation model.

• --rm_small_clusters

  Remove clusters that have less than rm_small_clusters.

• --qbx_thr

  Thresholds for QuickBundlesX.

• --num_threads

  Number of threads to be used for OpenMP parallelization. If None (default) the value of OMP_NUM_THREADS environment variable is used if it is set, otherwise all available threads are used. If < 0 the maximal number of threads minus \(|num_threads + 1|\) is used (enter -1 to use as many threads as possible). 0 raises an error. Only metrics using OpenMP will use this variable.

• --greater_than

  Keep streamlines that have length greater than this value.

• --less_than

  Keep streamlines have length less than this value.

• --nb_pts

  Number of points for discretizing each streamline.

• --progressive

  True to enable progressive registration.

Output Options

• --out_dir

  Output directory. (default current directory)

• --out_moved

  Filename of moved tractogram.

• --out_affine

  Filename of affine for SLR transformation.

• --out_stat_centroids

  Filename of static centroids.

• --out_moving_centroids

  Filename of moving centroids.

• --out_moved_centroids

  Filename of moved centroids.

References

[1]

Eleftherios Garyfallidis, Demian Wassermann, and Maxime Descoteaux. Direct native-space fiber bundle alignment for group comparisons. In Joint Annual Meeting ISMRM-ESMRMB 2014 SMRT 23rd Annual Meeting. Milan, Italy, May 2014. International Society for Magnetic Resonance in Medicine (ISMRM).

[2]

Eleftherios Garyfallidis, Omar Ocegueda, Demian Wassermann, and Maxime Descoteaux. Robust and efficient linear registration of white-matter fascicles in the space of streamlines. NeuroImage, 117:124–140, August 2015. URL: https://doi.org/10.1016/j.neuroimage.2015.05.016, doi:10.1016/j.neuroimage.2015.05.016.

[3]

Eleftherios Garyfallidis, Marc-Alexandre Côté, François Rheault, Jasmeen Sidhu, Janice Hau, Laurent Petit, David Fortin, Stephen Cunanne, and Maxime Descoteaux. Recognition of white matter bundles using local and global streamline-based registration and clustering. NeuroImage, 170:283–295, April 2018. Segmenting the Brain. URL: https://doi.org/10.1016/j.neuroimage.2017.07.015, doi:10.1016/j.neuroimage.2017.07.015.

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.