dipy_bundlewarp#

Synopsis#

BundleWarp: streamline-based nonlinear registration.

BundleWarp [1] is a nonrigid registration method for deformable registration of white matter tracts.

Usage#

dipy_bundlewarp [OPTIONS] static_file moving_file

Input Parameters#

  • static_file

    Path to the static (reference) .trk file.

  • moving_file

    Path to the moving (target to be registered) .trk file.

General Options#

  • --dist

    Path to the precalculated distance matrix file. (default: None)

  • --alpha

    Represents the trade-off between regularizing the deformation and having points match very closely. Lower value of alpha means high deformations. It is represented with λ in BundleWarp paper. NOTE: setting alpha<=0.01 will result in highly deformable registration that could extremely modify the original anatomy of the moving bundle. (default: 0.3)

  • --beta

    Represents the strength of the interaction between points Gaussian kernel size. (default: 20)

  • --max_iter

    Maximum number of iterations for deformation process in ml-CPD method. (default: 15)

  • --affine

    If False, use rigid registration as starting point. (default True) (default: True)

Output Options#

  • --out_dir

    Output directory. (default: current directory)

  • --out_linear_moved

    Filename of linearly moved bundle. (default: linearly_moved.trk)

  • --out_nonlinear_moved

    Filename of nonlinearly moved (warped) bundle. (default: nonlinearly_moved.trk)

  • --out_warp_transform

    Filename of warp transformations generated by BundleWarp. (default: warp_transform.npy)

  • --out_warp_kernel

    Filename of regularization gaussian kernel generated by BundleWarp. (default: warp_kernel.npy)

  • --out_dist

    Filename of MDF distance matrix. (default: distance_matrix.npy)

  • --out_matched_pairs

    Filename of matched pairs; streamline correspondences between two bundles. (default: matched_pairs.npy)

References#

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.