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Application and progress of machine learning in coronary computed tomography angiography
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Zi-Nuan Liu1, 2, Jun-Jie Yang1, *, Yun-Dai Chen1
Medical Journal of Chinese People’s Liberation Army | 2021, 46(3) : 286 - 293
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Medical Journal of Chinese People’s Liberation Army | 2021, 46(3): 286-293
• Review •
Application and progress of machine learning in coronary computed tomography angiography
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Zi-Nuan Liu1, 2, Jun-Jie Yang1, *, Yun-Dai Chen1
Affiliations
  • 1Department of Cardiovascular Medicine, the First Medical Center of Chinese PLA General Hospital, Beijing 100853, China
  • 2School of Medicine, Nankai University, Tianjin 300071, China
Published: 2021-03-28 doi: 10.11855/j.issn.0577-7402.2021.03.12
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Cardiac computed tomography angiography (CCTA) has become an important non-invasive method to evaluate coronary artery disease. With the extensive application and increased image analysis features, more demands on operational technique and efficiency are asked. Machine learning (ML) is the subarea of artificial intelligence (AI), which is completely data driven, by computer algorithm to identify and analyze the potential relationship of centralized variables in large data sets for realizing the prediction of external data. In the field of cardiac CT, the application of various ML algorithms would improve the efficiency and quality of CCTA, helping accurate lesion assessment and risk stratification. It also brings new applications in cardiac functional imaging. The applications of ML in cardiac CT have been reviewed in present paper including CT-image analysis, risk stratification, CT-myocardial perfusion and CT-fractional flow reserve.

artificial intelligence  /  machine learning  /  tomography, X-ray computed  /  coronary artery disease
Zi-Nuan Liu, Jun-Jie Yang, Yun-Dai Chen. Application and progress of machine learning in coronary computed tomography angiography[J]. Medical Journal of Chinese People’s Liberation Army, 2021 , 46 (3) : 286 -293 . DOI: 10.11855/j.issn.0577-7402.2021.03.12
Funding
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  • National Key Research and Development Program of China(2016YFC1300304)
  • Beijing NOVA Program(Z181100006218055)
  • Medical Big Data Program of PLAGH(2019MBD035)
Appendix
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Year 2021 volume 46 Issue 3
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Article Info
doi: 10.11855/j.issn.0577-7402.2021.03.12
  • Receive Date：2020-07-16
  • Online Date：2025-12-26
  • Published：2021-03-28
Article Data
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History
  • Received：2020-07-16
  • Revised：2020-10-26
Funding
National Key Research and Development Program of China(2016YFC1300304)
Beijing NOVA Program(Z181100006218055)
Medical Big Data Program of PLAGH(2019MBD035)
Affiliations
    1Department of Cardiovascular Medicine, the First Medical Center of Chinese PLA General Hospital, Beijing 100853, China
    2School of Medicine, Nankai University, Tianjin 300071, China

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