Fully automated artificial intelligence-based coronary CT angiography image processing: efficiency, diagnostic capability, and risk stratification

Zhang, Yaping; Feng, Yan; Sun, Jianqing; Zhang, Lu; Ding, Zhenhong; Wang, Lingyun; Zhao, Keke; Pan, Zhijie; Li, Qingyao; Guo, Ning; Xie, Xueqian

doi:10.1007/s00330-023-10494-6

Eur Radiol

2024

DOI: 10.1007/s00330-023-10494-6

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Fully automated artificial intelligence-based coronary CT angiography image processing: efficiency, diagnostic capability, and risk stratification

Yaping Zhang,

Yan Feng,

Jianqing Sun

et al.

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Revolutionizing Cardiac Imaging: A Scoping Review of Artificial Intelligence in Echocardiography, CTA, and Cardiac MRI

Moradi,

Olanisa,

Nzeako

et al. 2024

J. Imaging

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Background and Introduction: Cardiac imaging is crucial for diagnosing heart disorders. Methods like X-rays, ultrasounds, CT scans, and MRIs provide detailed anatomical and functional heart images. AI can enhance these imaging techniques with its advanced learning capabilities. Method: In this scoping review, following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) Guidelines, we searched PubMed, Scopus, Web of Science, and Google Scholar using related keywords on 16 April 2024. From 3679 articles, we first screened titles and abstracts based on the initial inclusion criteria and then screened the full texts. The authors made the final selections collaboratively. Result: The PRISMA chart shows that 3516 articles were initially selected for evaluation after removing duplicates. Upon reviewing titles, abstracts, and quality, 24 articles were deemed eligible for the review. The findings indicate that AI enhances image quality, speeds up imaging processes, and reduces radiation exposure with sensitivity and specificity comparable to or exceeding those of qualified radiologists or cardiologists. Further research is needed to assess AI’s applicability in various types of cardiac imaging, especially in rural hospitals where access to medical doctors is limited. Conclusions: AI improves image quality, reduces human errors and radiation exposure, and can predict cardiac events with acceptable sensitivity and specificity.

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Revolutionizing Cardiac Imaging: A Scoping Review of Artificial Intelligence in Echocardiography, CTA, and Cardiac MRI

Moradi,

Olanisa,

Nzeako

et al. 2024

J. Imaging

View full text Add to dashboard Cite

show abstract

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Fully automated artificial intelligence-based coronary CT angiography image processing: efficiency, diagnostic capability, and risk stratification

Cited by 1 publication

References 37 publications

Revolutionizing Cardiac Imaging: A Scoping Review of Artificial Intelligence in Echocardiography, CTA, and Cardiac MRI

Revolutionizing Cardiac Imaging: A Scoping Review of Artificial Intelligence in Echocardiography, CTA, and Cardiac MRI

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