Keywords: Vessels, Cardiovascular, Deep LearningThis study aims to investigate the feasibility of a compressed sensing artificial intelligence (CSAI) framework for non-contrast-enhanced coronary MRA. The image quality and the diagnostic performance of CSAI coronary MRA in patients with suspected CAD were fully evaluated using coronary computed tomography angiography (CTA) as the non-invasive clinical reference standard. The results shows that all recruited patients completed coronary MRA with high image quality and diagnostic performance within short scan time. Therefore, we conclude that the CASI coronary MRA could be a robust and safe non-invasive alternative for excluding significant disease in patients with suspected CAD.
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