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Abstract #2546

Accelerating Compressed Sensing MRI Reconstruction with GPU Computing

David S. Smith1,2, John C. Gore1,2, Edward Brian Welch1,2

1Radiology & Radiological Sciences, Vanderbilt University, Nashville, TN, United States; 2Institute of Imaging Science, Vanderbilt University, Nashville, TN, United States

We show that compressed sensing MRI reconstruction using a Cartesian split Bregman solver can be dramatically accelerated using GPU computing. We find a factor of ~30 speedup for images of square dimension 512 and higher on a system based on an NVIDIA Tesla C2050 GPU card and Accelereye's Jacket GPU wrapper for MATLAB.