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Abstract #3354

Greater Acceleration Through Sparsity-Promoting GRAPPA Kernel Calibration

Daniel S. Weller1, Jonathan R. Polimeni2, 3, Leo Grady4, Lawrence L. Wald2, 3, Elfar Adalsteinsson1, Vivek Goyal1

1EECS, Massachusetts Institute of Technology, Cambridge, MA, United States; 2A. A. Martinos Center, Dept. of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; 3Dept. of Radiology, Harvard Medical School, Boston, MA, United States; 4Dept. of Image Analytics and Informatics, Siemens Corporate Research, Princeton, NJ, United States


When applying GRAPPA at high accelerations, it is not always feasible to acquire sufficiently many auto-calibration signal (ACS) lines to properly calibrate the interpolation kernels. The proposed calibration method employs regularization promoting joint sparsity of the coil images that would be reconstructed. This method improves reconstruction quality and increases the total acceleration that is achievable with GRAPPA.

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