We are sharing low-rank plus sparse (L+S) reconstruction for undersampled dynamic MRI.
The L+S model offers greater compressibility than either a sparse or a low-rank model on its own. The reconstruction enables separation of contrast enhancement from background and automated background suppression without subtraction modeling.
The MATLAB code includes core reconstruction algorithms and examples using Cartesian and golden-angle radial data sets.
Low-rank plus sparse matrix decomposition for accelerated dynamic MRI with separation of background and dynamic components.
Magn Reson Med. 2015 Mar;73(3):1125-36. doi: 10.1002/mrm.25240
Please cite this work if you are using L+S reconstruction 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 (Ricardo Otazo) 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 Ricardo Otazo, PhD.