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Abstract #3794

AMP-SENSE: Parallel Imaging Compressed Sensing with Approximate Message Passing

Evan Levine1, 2, Kyunghyun Sung3, Manojkumar Saranathan2, Bruce Daniel2, Brian Andrew Hargreaves2

1Electrical Engineering, Stanford University, Palo Alto, CA, United States; 2Radiology, Stanford University, Palo Alto, CA, United States; 3Radiological Sciences, University of California, Los Angeles, Los Angeles, CA, United States

Iterative Soft Thresholding (IST) and a more recent method, Approximate Message Passing (AMP) are promising techniques for fast compressed sensing (CS) reconstruction. Combining CS, parallel imaging, partial-Fourier, and other techniques is still being investigated, and the reconstruction time is critical. The AMP method, as is currently implemented on a single coil basis, does not exploit known dependencies among coil images. We have developed a novel reconstruction method, AMP-SENSE, that incorporates coil sensitivity information into AMP to address the combined CS and parallel imaging problem, improving both performance and computational efficiency. We demonstrate an application to dynamic contrast-enhanced (DCE) breast MRI.