Abstract #4201

Ricardo Otazo^{1}, Riccardo Lattanzi^{1},
Daniel K. Sodickson^{1}

^{1}Bernard and Irene Schwartz Center for
Biomedical Imaging, NYU School of Medicine, New York, NY, United States

The limits of acceleration for combinations of compressed sensing and parallel imaging remain uncertain. In this work, we investigate the performance of the combined reconstruction with respect to the number of coils for truly-sparse and compressible MR images. A complete basis set of electromagnetic fields is employed as a hypothetical optimal coil array, which achieves the best possible SNR for parallel imaging reconstructions. We demonstrate that the minimum number of required k-space samples is bounded by the number of sparse coefficients, which removes the oversampling factor of 3-5 for compressed sensing alone and approximates the theoretical bounds of L0-norm minimization.