Sbastien Roujol1, Tamer A. Basha1, Christophe Schlke1, 2, Martin Buehrer1, 2, Warren J. Manning1, 3, Reza Nezafat1
1Medecine, BIDMC / Harvard Medical School, Boston, MA, United States; 2Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland; 3Radiology, BIDMC / Harvard Medical School, Boston, MA, United States
In cardiac MR perfusion after physiological stress a significant respiratory motion is encountered and coil sensitivity maps are generally corrupted due to patient motion during exercise. Compressed sensing (CS) is an alternative acceleration technique that enables high acceleration even without exploiting temporal dimension or need for coil maps. However, iterative CS reconstruction is lengthy, performed off-line and is not usually integrated into the workflow of a clinical scan. In this study, a GPU-based workflow and a CPU cluster-based workflow have been developed and compared to accelerate the iterative CS reconstruction and minimize the overall reconstruction latency.