The USC Andrew and Erna Viterbi School of Engineering USC Signal and Image Processing Institute USC Ming Hsieh Department of Electrical and Computer Engineering University of Southern California

Technical Report USC-SIPI-443

“LORAKS Software Version 2.0: Faster Implementation and Enhanced Capabilities ”

by Tae Hyung Kim and Justin P. Haldar

May 2018

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 (LOw-RAnk modeling of local K-Space neighborhoods). 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 present technical report (and supplementary material available for download at, we describe an updated public open-source software release that provides access to many of the new developments we’ve made since 2014, including substantially-faster algorithms and a variety of new formulations of the inverse problem.

To download the report in PDF format click here: USC-SIPI-443.pdf (3.3Mb)