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k-t SPARSE-SENSE MATLAB Code

Combined parallel imaging and compressed sensing reconstruction for accelerated perfusion MRI.

We are sharing a combined compressed sensing and parallel imaging reconstruction for accelerated dynamic MRI.

The algorithm merges k-t SPARSE—a high-frame-rate imaging technique that exploits spatio-temporal sparsity—with sensitivity encoding (SENSE) reconstruction to substantially increase the acceleration rate for perfusion imaging.

The MATLAB code includes reconstruction algorithms and examples of cardiac cine and perfusion MRI. The non-linear reconstruction algorithm was implemented using conjugate gradient and iterative soft-thresholding. For more information, see the related publication.

Related Publication

Otazo R, Kim D, Axel L, Sodickson DK.
Combination of compressed sensing and parallel imaging for highly accelerated first-pass cardiac perfusion MRI.
Magn Reson Med. 2010 Sep;64(3):767-76. doi: 10.1002/mrm.22463

Please cite this work if you are using k-t SPARSE-SENSE 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.

Please spell out your affiliation (e.g. "New York University" rather than "NYU").

Contact

Questions about this resource may be directed to Ricardo Otazo, PhD.