/hdft-subsampled-recon

Computes a transformation of multi-shell diffusion weighted data to a set of Spherical Harmonic coefficients and outputs 4D Spherical Harmonic coefficient data. This is a first step in the Schneider Lab HDFT diffusion reconstruction process.

Primary LanguagePython

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hdft-subsampled-recon

Build context for a Flywheel compatible Gear for the HDFT Subsampled Recon algorithm from Schneider Lab, University of Pittsburgh.

This sample code computes a transformation of multi-shell diffusion weighted data to a set of Spherical Harmonic coefficients. Outputs 4D Spherical Harmonic coefficient data. This is a first step in the Schneider Lab HDFT diffusion reconstruction process.

Inputs

  • dwi_filename: input filename of 4D DWI data
  • subsampling_vec: input vector to select volumes from dwi_filename (can be a text file or CSV)
  • bvals_filename: input file of Nx1 b values
  • bvecs_filename: input file of Nx3 b vectors

Parameters

  • spherical_harmonics_order: The maximum order of spherical harmonics. Defaulted to 8.
  • mean_diffusion_length: The mean diffusion length for reconstruction of GQI matrix. Defaulted to 1.2.

Output

  • sh_filename: 4D Spherical Harmonic coefficient data.

Reference

Pathak, S. K., Fissell, C., Krishnaswamy, D., Aggarwal, S., Hachey, R., Schneider, W. (2015). Diffusion reconstruction by combining spherical harmonics and generalized q-sampling imaging. ISMRM, Toronto, Canada.

License

All code is copyright University of Pittsburgh unless alternate authorship noted. This code is not for public distribution, please contact Schneider Lab re distribution. http://www.lrdc.pitt.edu/schneiderlab/