Xiao Chen1, Michael Salerno2, 3, Patrick F. Antkowiak1, Frederick H. Epstein1, 2
1Biomedical Engineering, University of Virginia, Charlottesville, VA, United States; 2Radiology, University of Virginia, Charlottesville, VA, United States; 3Cardiology, University of Virginia, Charlottesville, VA, United States
Many MR image series present temporal sparsity, in which image signal intensity changes smoothly through time, and such images are inherently suitable for acceleration using compressed sensing (CS) reconstruction. However, object motion between images violates temporal smoothness constraints and significantly degrades the quality of the CS-reconstructed images. To overcome this problem, we propose a general motion-guided CS algorithm which tracks object motion and guides the CS sparsity transform along the direction of motion. Improved image quality was observed using the proposed algorithm in dynamic contrast-enhanced images compared to non-motion guided reconstruction at an acceleration rate of 4.
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