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“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 http://mr.usc.edu/download/LORAKS2/), 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.