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Machine Learning for Assessment of Coronary Artery Disease in Cardiac CT: A Survey
2019
Frontiers in Cardiovascular Medicine
Cardiac computed tomography (CT) allows rapid visualization of the heart and coronary arteries with high spatial resolution. However, analysis of cardiac CT scans for manifestation of coronary artery disease is time-consuming and challenging. Machine learning (ML) approaches have the potential to address these challenges with high accuracy and consistent performance. In this mini review, we present a survey of the literature on ML-based analysis of coronary artery disease in cardiac CT. We
doi:10.3389/fcvm.2019.00172
pmid:32039237
pmcid:PMC6988816
fatcat:tsq6vf3vi5a4rjxoxzqy7xd5tu