人工智能
医学
深度学习
狭窄
机器学习
分割
放射科
计算机科学
作者
Xinhong Zhang,Boyan Zhang,Fan Zhang
出处
期刊:Angiology
[SAGE]
日期:2023-07-03
卷期号:75 (5): 405-416
标识
DOI:10.1177/00033197231187063
摘要
The aim of this review is to introduce some applications of artificial intelligence (AI) algorithms for the detection and quantification of coronary stenosis using computed tomography angiography (CTA). The realization of automatic/semi-automatic stenosis detection and quantification includes the following steps: vessel central axis extraction, vessel segmentation, stenosis detection, and quantification. Many new AI techniques, such as machine learning and deep learning, have been widely used in medical image segmentation and stenosis detection. This review also summarizes the recent progress regarding coronary stenosis detection and quantification, and discusses the development trends in this field. Through evaluation and comparison, researchers can better understand the research frontier in related fields, compare the advantages and disadvantages of various methods, and better optimize the new technologies. Machine learning and deep learning will promote the process of automatic detection and quantification of coronary artery stenosis. However, the machine learning and the deep learning methods need a large amount of data, so they also face some challenges because of the lack of professional image annotations (manually add labels by experts).
科研通智能强力驱动
Strongly Powered by AbleSci AI