Application of Artificial Intelligence to Cardiovascular Computed Tomography

被引：8
作者：
Yang, Dong Hyun [1 ,2 ]
机构：
[1] Univ Ulsan, Coll Med, Asan Med Ctr, Cardiac Imaging Ctr,Dept Radiol, 88 Olymp Ro 43 Gil, Seoul 05505, South Korea
[2] Univ Ulsan, Coll Med, Asan Med Ctr, Cardiac Imaging Ctr,Res Inst Radiol, 88 Olymp Ro 43 Gil, Seoul 05505, South Korea
来源：
KOREAN JOURNAL OF RADIOLOGY | 2021年 / 22卷 / 10期
关键词：
CT; Artificial intelligence; Deep learning; Heart; FRACTIONAL FLOW RESERVE; CT ANGIOGRAPHY; CARDIAC CT; DIAGNOSTIC PERFORMANCE; NOISE-REDUCTION; SEGMENTATION; NETWORKS; DISEASE;
D O I：
10.3348/kjr.2020.1314
中图分类号：
R8 [特种医学]; R445 [影像诊断学];
学科分类号：
1002 ; 100207 ; 1009 ;
摘要：
Cardiovascular computed tomography (CT) is among the most active fields with ongoing technical innovation related to image acquisition and analysis. Artificial intelligence can be incorporated into various clinical applications of cardiovascular CT, including imaging of the heart valves and coronary arteries, as well as imaging to evaluate myocardial function and congenital heart disease. This review summarizes the latest research on the application of deep learning to cardiovascular CT. The areas covered range from image quality improvement to automatic analysis of CT images, including methods such as calcium scoring, image segmentation, and coronary artery evaluation.
引用
收藏
页码：1597 / 1608
页数：12
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