Ricardo Otazo1, Daniel Kim1, Daniel K. Sodickson1
1Center for Biomedical Imaging, NYU School of Medicine, New York, NY, USA
Compressed sensing and parallel imaging are combined into a single joint reconstruction paradigm named k-t Parallel-Sparse for highly accelerated first pass cardiac perfusion imaging. The method exploits the joint sparsity in the sensitivity-encoded images to achieve higher accelerations than for coil-by-coil sparsity alone, and it does not require dynamic training data. We demonstrate the feasibility of high in vivo acceleration factors of 8 and 12 and assess the effect of respiratory motion.