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Abstract #3801

Dual Projected Background Nulling Compressed Sensing for Robust Separation of Dynamic Contrast-Enhanced Angiograms

Suhyung Park 1 , Eung Yeop Kim 2 , and Jaeseok Park 3

1 Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Sungkyunkwan University, Suwon, Gyeong Gi-Do, Korea, 2 Department of Radiology, Gachon University Gil Medical Center, Incheon, Korea, 3 Biomedical Imaging and Engineering Lab., Department of Global Biomedical Engineering, Sungkyunkwan University, Suwon, Gyeong Gi-Do, Korea

Dynamic contrast-enhanced magnetic resonance angiography (DCE-MRA) requires high spatiotemporal resolution, and typically employs subtraction between static reference and dynamic images followed by maximum intensity projection (MIP) to visualize time-varying angiograms. Nevertheless, the subtraction-based DCE-MRA suffers from incomplete suppression of background signals in the presence of motion-induced voxel misregistration, potentially impairing the detectability of small distal vessels. In this work, we propose a novel reconstruction framework, dual projected background nulling compressed sensing (BANC), for robust separation of dynamic contrast-enhanced angiograms, in which we decompose x-t images into background static tissue signals (low rank component), background motion-induced signals (sparse component I), and DCE angiograms of interest (sparse component II) and then jointly estimate them while selectively nulling multiple background signals. Simulations and experiments validate that the proposed method is, if compared with conventional methods, highly effective in generating dynamic angiograms with robust background suppression even at very high reduction factors (R~30).

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