We are sharing MATLAB code for model-based diffusion tensor imaging (TDI) reconstruction with variational constraints on the tensor elements.
The method uses redundancies present in diffusion-weighted image data to reduce the number of unknowns in the optimization problem. A total-variation constrain imposed on the elements of the diffusion tensor enables compressed sensing to be performed directly in the target quantitative domain.
For more information, see the related publication.
A model-based reconstruction for undersampled radial spin-echo DTI with variational penalties on the diffusion tensor.
NMR Biomed. 2015 Mar;28(3):353-66. doi: 10.1002/nbm.3258
Please cite this work if you are using model-based DTI reconstruction with variational constraints in your research.
Get the Code
The software available on this page is provided free of charge and comes without any warranty. CAI²R and NYU Grossman School of Medicine do not take any liability for problems or damage of any kind resulting from the use of the files provided. Operation of the software is solely at the user’s own risk. The software developments provided are not medical products and must not be used for making diagnostic decisions.
The software is provided for non-commercial, academic use only. Usage or distribution of the software for commercial purpose is prohibited. All rights belong to the author (Florian Knoll) and NYU Grossman School of Medicine. If you use the software for academic work, please give credit to the author in publications and cite the related publications.
Questions about this resource may be directed to Florian Knoll, PhD.