LORAKS 2.0: Implementation and Examples

Update: June 10, 2019.  The software available from this page has been updated from Version 2.0 to Version 2.1.  This new version makes a minor change to substantially reduce memory usage and improve computational efficiency for algorithm 4 (the multiplicative half-quadratic algorithm that uses FFTs with approximation).  The original Version 2.0 is still available on request, although we encourage the use of Version 2.1.

This page provides a new MATLAB software implementation for Low-Rank Modeling of Local k-Space Neighborhoods (LORAKS), as described in the technical report:

T. H. Kim, J. P. Haldar.
LORAKS Software Version 2.0: Faster Implementation and Enhanced Capabilities.
University of Southern California, Los Angeles, CA,
Technical Report USC-SIPI-443, May 2018.
[link]

Over the past several years, our research group has been developing a novel structured low-rank matrix modeling framework for magnetic resonance (MR) image reconstruction that we call LORAKS. In the spirit of reproducible research, we had previously released a public open-source software implementation of LORAKS-based image reconstruction in 2014. In the new technical report referenced above (and supplementary material available for download below), we provide access to an updated open-source software release that includes many of the new LORAKS developments that have occurred since 2014, including substantially-faster algorithms and a variety of new formulations of the inverse problem. The download also includes examples of real in vivo MRI k-space data corresponding to human brain images.

An example reconstruction result is shown below, in which we have used P-LORAKS to reconstruct MRI brain data from highly-accelerated calibrationless 4-channel parallel imaging data.

Gold Standard Calibrationless Sampling
Zero-filled P-LORAKS

The software and data can be downloaded using the form below:

Download

    Permission to use, copy, modify, and distribute this software and its documentation for educational, research and non-profit purposes, without fee, and without a written agreement is hereby granted, provided that the above copyright notice, this paragraph and the following three paragraphs appear in all copies. If you use this code or its derivatives in your own work, you are required to cite at least the LORAKS V2.0 technical report as well as the original LORAKS references corresponding to the problem formulations you have used.

    Permission to make commercial use of this software may be obtained by contacting:
    USC Stevens Center for Innovation
    University of Southern California
    1150 S. Olive Street, Suite 2300
    Los Angeles, CA 90115, USA

    This software program and documentation are copyrighted by The University of Southern California. The software program and documentation are supplied "as is", without any accompanying services from USC. USC does not warrant that the operation of the program will be uninterrupted or error-free. The end-user understands that the program was developed for research purposes and is advised not to rely exclusively on the program for any reason.

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