1Electrical Engineering, University of Southern California, Los Angeles, CA, United States, 2Radiology, Harvard Medical School, Boston, MA, United States
We introduce a novel framework called SENSE-LORAKS for partial Fourier phase-constrained parallel MRI reconstruction. SENSE-LORAKS combines classical SENSE data modeling with advanced regularization based on the novel low-rank modeling of local k-space neighorhoods (LORAKS) framework. Unlike conventional phase-constrained SENSE techniques, SENSE-LORAKS enables use of phase constraints without requiring a prior estimate of the image phase or a fully sampled region of k-space that could be used for phase autocalibration. Compared to previous SENSE-based and LORAKS-based reconstruction approaches, SENSE-LORAKS is compatible with a much wider range of sampling trajectories, which can be leveraged to achieve much higher acceleration rates.
