dipy_fit_ivim#

Synopsis#

Workflow for Intra-voxel Incoherent Motion reconstruction and for computing IVIM metrics.

Performs a IVIM reconstruction [1], [2] on the files by ‘globing’ input_files and saves the IVIM metrics in a directory specified by out_dir.

Usage#

dipy_fit_ivim [OPTIONS] input_files bvalues_files bvectors_files mask_files

Input Parameters#

  • input_files

    Path to the input volumes. This path may contain wildcards to process multiple inputs at once.

  • bvalues_files

    Path to the bvalues files. This path may contain wildcards to use multiple bvalues files at once.

  • bvectors_files

    Path to the bvalues files. This path may contain wildcards to use multiple bvalues files at once.

  • mask_files

    Path to the input masks. This path may contain wildcards to use multiple masks at once. (default: No mask used)

General Options#

  • --split_b_D

    Value to split the bvals to estimate D for the two-stage process of fitting.

  • --split_b_S0

    Value to split the bvals to estimate S0 for the two-stage process of fitting.

  • --b0_threshold

    Threshold value for the b0 bval.

  • --save_metrics

    List of metrics to save. Possible values: S0_predicted, perfusion_fraction, D_star, D

Output Options#

  • --out_dir

    Output directory. (default current directory)

  • --out_S0_predicted

    Name of the S0 signal estimated to be saved.

  • --out_perfusion_fraction

    Name of the estimated volume fractions to be saved.

  • --out_D_star

    Name of the estimated pseudo-diffusion parameter to be saved.

  • --out_D

    Name of the estimated diffusion parameter to be saved.

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.