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A Deep Learning Segmentation Approach in Free-Breathing Real-Time Cardiac Magnetic Resonance Imaging.

Fan Yang | Yan Zhang | Pinggui Lei | Lihui Wang | Yuehong Miao | Hong Xie | Zhu Zeng
BioMed research international | 2019

The purpose of this study was to segment the left ventricle (LV) blood pool, LV myocardium, and right ventricle (RV) blood pool of end-diastole and end-systole frames in free-breathing cardiac magnetic resonance (CMR) imaging. Automatic and accurate segmentation of cardiac structures could reduce the postprocessing time of cardiac function analysis.

Pubmed ID: 31467898

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