dipy_fit_forecast

Synopsis

Workflow for Fiber ORientation Estimated using Continuous Axially Symmetric Tensors (FORECAST).

FORECAST [1], [2], [3] is a Spherical Deconvolution reconstruction model for multi-shell diffusion data which enables the calculation of a voxel adaptive response function using the Spherical Mean Technique (SMT) [2], [3].

Usage

dipy_fit_forecast [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 bvectors 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

• --lambda_lb

  Regularization parameter for the Laplacian-Beltrami operator. (default: 0.001)

• --dec_alg

  Spherical deconvolution algorithm. The possible values are Weighted Least Squares (‘WLS’), Positivity Constraints using CVXPY (‘POS’) and the Constraint Spherical Deconvolution algorithm (‘CSD’). (default: CSD)

• --lambda_csd

  Regularization parameter for the CSD algorithm. (default: 1.0)

• --sphere_name

  Sphere name on which to reconstruct the fODFs. (default: None)

• --b0_threshold

  Threshold used to find b0 volumes. (default: 50.0)

• --bvecs_tol

  Bvecs should be unit vectors. (default: 0.01)

• --sh_order_max

  Maximum spherical harmonics order (l) used in the SFM fit. (default: 8)

• --relative_peak_threshold

  Only return peaks greater than relative_peak_threshold * m where m is the largest peak. (default: 0.5)

• --min_separation_angle

  The angle tolerance between directions. (default: 25)

• --parallel

  Whether to use parallelization in peak-finding. (default: False)

• --extract_pam_values

  Save or not to save pam volumes as single nifti files. (default: False)

• --num_processes

  If parallel is True, the number of subprocesses to use (default: None)

Output Options

• --out_dir

  Output directory. (default: current directory)

• --out_pam

  Name of the peaks volume to be saved. (default: peaks.pam5)

• --out_shm

  Name of the spherical harmonics volume to be saved. (default: shm.nii.gz)

• --out_peaks_dir

  Name of the peaks directions volume to be saved. (default: peaks_dirs.nii.gz)

• --out_peaks_values

  Name of the peaks values volume to be saved. (default: peaks_values.nii.gz)

• --out_peaks_indices

  Name of the peaks indices volume to be saved. (default: peaks_indices.nii.gz)

• --out_gfa

  Name of the generalized FA volume to be saved. (default: gfa.nii.gz)

• --out_sphere

  Sphere vertices name to be saved. (default: sphere.txt)

• --out_b

  Name of the B Matrix to be saved. (default: B.nii.gz)

• --out_qa

  Name of the Quantitative Anisotropy to be saved. (default: qa.nii.gz)

References

[1]

Adam W. Anderson. Measurement of fiber orientation distributions using high angular resolution diffusion imaging. Magnetic Resonance in Medicine, 54(5):1194–1206, 2005. URL: https://doi.org/10.1002/mrm.20667, doi:10.1002/mrm.20667.

[2] (1,2)

Enrico Kaden, Frithjof Kruggel, and Daniel C. Alexander. Quantitative mapping of the per-axon diffusion coefficients in brain white matter. Magnetic Resonance in Medicine, 75(4):1752–1763, April 2016. URL: https://doi.org/10.1002/mrm.25734, doi:10.1002/mrm.25734.

[3] (1,2)

Mauro Zucchelli, Maxime Descoteaux, and Gloria Menegaz. A generalized SMT-based framework for Diffusion MRI microstructural model estimation. In Enrico Kaden, Francesco Grussu, Lipeng Ning, Chantal M. W. Tax, and Jelle Veraart, editors, Computational Diffusion MRI, 51–63. Cham, 2018. Springer International Publishing.

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.