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Abstract #0880

Accelerated first-pass perfusion MRI using BLOSM: Evaluation using dynamic simulations and patient datasets with prominent respiratory motion

Xiao Chen 1 , Yang Yang 1 , Michael Salerno 2,3 , and Frederick H. Epstein 1

1 Biomedical Engineering, University of Virginia, Charlottesville, VA, United States, 2 Radiology, University of Virginia, Charlottesville, VA, United States, 3 Cardiology, University of Virginia, Charlottesville, VA, United States

We recently developed a motion-compensated compressed sensing (CS) method to accelerate dynamic MRI of the heart that exploits matrix low-rank sparsity within motion-tracked regions of temporal image sequences (Block LOw-rank Sparsity with Motion guidance, or BLOSM). Initial results showed that BLOSM appears promising for accelerating first-pass myocardial perfusion imaging, even when substantial respiratory motion occurs. Presently, we implemented improved motion tracking for BLOSM and compared the improved BLOSM method to other CS methods using computer-simulated motions and using first-pass perfusion datasets from patients with respiratory motion.

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