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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