Meeting Banner
Abstract #2652

Elora: Enforcing Low Rank for Parallel MR Reconstruction

Jun Liu1, Axel Loewe1, Michael O. Zenge2, Alban Lefebvre1, Edgar Mueller2, Mariappan S. Nadar1

1Imaging and Computer Vision, Siemens Corporation, Corporate Technology, Princeton, NJ, United States; 2MR Application & Workflow Development, Siemens AG, Healthcare Sector, Erlangen, Bavaria, Germany

Parallel imaging exploits the difference in sensitivities between individual coil elements in a receive array to reduce the number of gradient encodings required for imaging. SENSE and GRAPPA are two representative approaches. In this abstract, a new approach, called Elora is proposed. Elora implicitly uses coil sensitivities by estimating a low rank subspace from the calibration data, and then works by enforcing the low rank constraint on the sliding blocks of the k-space data.