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中华诊断学电子杂志 ›› 2023, Vol. 11 ›› Issue (03) : 153 -157. doi: 10.3877/cma.j.issn.2095-655X.2023.03.002

心血管疾病诊治

基于血管内超声的机器学习在冠状动脉病变中的研究进展
熊鑫, 邓勇志()   
  1. 030024 太原,山西医科大学附属心血管病医院,山西省心血管病医院(研究所),山西省心血管病临床医学研究中心心脏大血管外科
  • 收稿日期:2023-02-13 出版日期:2023-08-26
  • 通信作者: 邓勇志
  • 基金资助:
    山西省医学重点科研重大科技攻关项目(2021XM04)

Advances in the application of machine learning based on intravascular ultrasound in coronary artery disease

Xin Xiong, Yongzhi Deng()   

  1. Department of Cardiovascular Surgery, the Affiliated Cardiovascular Hospital of Shanxi Medical University, Shanxi Cardiovascular Hospital (Institute), Shanxi Clinical Medical Research Center of Cardiovascular Disease, Taiyuan 030024, China
  • Received:2023-02-13 Published:2023-08-26
  • Corresponding author: Yongzhi Deng
引用本文:

熊鑫, 邓勇志. 基于血管内超声的机器学习在冠状动脉病变中的研究进展[J]. 中华诊断学电子杂志, 2023, 11(03): 153-157.

Xin Xiong, Yongzhi Deng. Advances in the application of machine learning based on intravascular ultrasound in coronary artery disease[J]. Chinese Journal of Diagnostics(Electronic Edition), 2023, 11(03): 153-157.

血管内超声图像是心血管疾病临床诊疗的重要参考数据。医生对血管内超声图像信息的判断在冠状动脉病变的诊断和治疗方面具有重要作用。机器学习能够提取出人肉眼无法感知的图像信息,进行数据分析并构建医学诊断模型,有助于判定斑块的稳定性,预测疾病进程以及患者的临床结局,在辅助临床工作方面有一定作用。笔者就机器学习方法在冠状动脉血管内超声图像的应用进展进行综述,并探讨其局限性及发展方向。

Intravascular ultrasound(IVUS) is an essential source of information for the clinical diagnosis and management of coronary artery disease. The diagnosis and management of coronary artery disease heavily relies on the medical professionals′ interpretation of IVUS images. Machine learning can analyze data, create medical diagnostic models, and extract information from IVUS images that human eyes cannot perceive. These capabilities help enhance the diagnosis of coronary artery disease, forecast patients′ disease states and clinical outcomes, and play a significant role in supporting clinical work. This article discusses the limitations and potential applications of machine learning techniques in IVUS for coronary artery imaging.

表1 不同ML在IVUS方面的应用
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