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Abstract #2824

Sequential Application of Parallel Imaging and Compressed Sensing

Philip James Beatty1, Kevin F. King2, Luca Marinelli3, Chris J. Hardy3, Michael Lustig4

1Applied Science Laboratory, GE Healthcare, Menlo Park, CA, USA; 2Applied Science Laboratory, GE Healthcare, Waukesha, WI, USA; 3Global Research Center, General Electric, Niskayuna, NY, USA; 4Electrical Engineering, Stanford University, Stanford, CA, USA

An alternative approach to combining parallel imaging (PI) and compressed sensing (CS) is proposed. The k-space sampling pattern is modified to allow parallel image and compressed sensing to be applied in separate sequential stages during image reconstruction. The proposed approach allows compressed sensing to be used with many proven and pre-existing parallel imaging techniques and has the potential to reduce the amount of computation required for PI+CS reconstructions.