dipy_fit_dki

Usage

dipy_fit_dki [-h] [–fit_method str] [–b0_threshold float] [–sigma float] [–save_metrics [str …]] [–out_dir str] [–out_dt_tensor str] [–out_fa str]

[–out_ga str] [–out_rgb str] [–out_md str] [–out_ad str] [–out_rd str] [–out_mode str] [–out_evec str] [–out_eval str] [–out_dk_tensor str] [–out_mk str] [–out_ak str] [–out_rk str] input_files bvalues_files bvectors_files mask_files

Workflow for Diffusion Kurtosis reconstruction and for computing DKI metrics. Performs a DKI reconstruction on the files by ‘globing’ input_files and saves the DKI metrics in a directory specified by out_dir.

Positional Arguments

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)

options:

-h, --help

show this help message and exit

--fit_method str

can be one of the following: ‘OLS’ or ‘ULLS’ for ordinary least squares ‘WLS’ or ‘UWLLS’ for weighted ordinary least squares

--b0_threshold float

Threshold used to find b0 volumes.

--sigma float

An estimate of the variance. [3] recommend to use 1.5267 * std(background_noise), where background_noise is estimated from some part of the image known to contain no signal (only noise)

–save_metrics [str …]

List of metrics to save. Possible values: fa, ga, rgb, md, ad, rd, mode, tensor, evec, eval

Output Arguments(Optional)

--out_dir str

Output directory. (default current directory)

--out_dt_tensor str

Name of the tensors volume to be saved.

--out_fa str

Name of the tensors volume to be saved.

--out_ga str

Name of the fractional anisotropy volume to be saved.

--out_rgb str

Name of the geodesic anisotropy volume to be saved.

--out_md str

Name of the color fa volume to be saved.

--out_ad str

Name of the mean diffusivity volume to be saved.

--out_rd str

Name of the axial diffusivity volume to be saved.

--out_mode str

Name of the radial diffusivity volume to be saved.

--out_evec str

Name of the mode volume to be saved.

--out_eval str

Name of the eigenvectors volume to be saved.

--out_dk_tensor str

Name of the eigenvalues to be saved.

--out_mk str

Name of the mean kurtosis to be saved.

--out_ak str

Name of the axial kurtosis to be saved.

--out_rk str

Name of the radial kurtosis to be saved.

References

[1]

Tabesh, A., Jensen, J.H., Ardekani, B.A., Helpern, J.A., 2011. Estimation of tensors and tensor-derived measures in diffusional kurtosis imaging. Magn Reson Med. 65(3), 823-836

[2]

Jensen, Jens H., Joseph A. Helpern, Anita Ramani, Hanzhang Lu, and Kyle Kaczynski. 2005. Diffusional Kurtosis Imaging: The Quantification of Non-Gaussian Water Diffusion by Means of Magnetic Resonance Imaging. MRM 53 (6):1432-40.

[3]

Chang, L-C, Jones, DK and Pierpaoli, C (2005). RESTORE: robust estimation of tensors by outlier rejection. MRM, 53: 1088-95.

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.