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Abstract #4906

Navigator-less manifold recovery of cardiac data using iterative SToRM

Yasir Q Mohsin1, Sunrita Poddar2, Bijoy Thattayilath3, Deidra Ansah3, and Mathews Jacob4

1Electrical and computer Engineering, University of Iowa, Iowa City, IA, United States, 2Electrical and COmputer Engineering, University of Iowa, Iowa City, IA, United States, 3Cardiology, University of Iowa, Iowa City, IA, United States, 4Electrical and computer Engineering, University of Iowa, Iow City, IA, United States

Self-gated acquisitions, which rely on navigator acquisitions, can offer shortened scan time and can enable cardiac imaging of patients who cannot hold their breath; they are emerging as promising alternatives to breath-held protocols. A challenge with such schemes is the inefficiencies associated with the navigator acquisition, as well as the need for complex and heuristic processing of the navigator signals to accurately determine the cardiac and respiratory phases. The focus of this work is to introduce a navigator-less acquisition and reconstruction strategy, built upon our recent work termed as SToRM, which exploits the manifold structure of images. The proposed framework eliminates the need for navigators in SToRM, in addition to enabling spatially localized manifold modeling, where the manifold structure can vary depending on the spatial structure.

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