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Abstract #0007

A Combined Approach to Compressed Sensing & Parallel Imaging for Fat-Water Separation with R2* Estimation

Curtis N. Wiens1, Colin M. McCurdy2, 3, Charles A. McKenzie, 13

1Department of Physics and Astronomy, University of Western Ontario, London, Ontario, Canada; 2Department of Physics, University of Guelph, Guelph, Ontario, Canada; 3Department of Medical Biophysics, University of Western Ontario, London, Ontario, Canada

R2*-corrected chemical shift based fat-water separation techniques have been used to accurately quantify fat. These are time-consuming and require image acceleration techniques. The following work describes a method of separating fat and water from undersampled multi-channel datasets. This method simultaneously applies compressed sensing, parallel imaging, and fat-water separation. To illustrate this technique, net acceleration factors of up to 4 are shown in the abdomen. Including the R2* term improves the accuracy of the fat-water separation. The proposed method improves image quality over sequential parallel imaging and fat-water separation at high acceleration factors.