基础医学与临床 ›› 2022, Vol. 42 ›› Issue (3): 360-365.doi: 10.16352/j.issn.1001-6325.2022.03.002

• 特邀专题:聚焦动脉粥样硬化斑块稳定性 • 上一篇    下一篇

血管内光学相干层析成像技术在冠状动脉粥样硬化斑块检测方面的应用

裘耀扬, 桂家辉, 黄林, 虎学强, 李勤*   

  1. 北京理工大学 生命学院, 北京 100081
  • 收稿日期:2021-12-30 修回日期:2022-01-09 出版日期:2022-03-05 发布日期:2022-03-04
  • 通讯作者: * liqin@bit.edu.cn
  • 基金资助:
    国家自然科学基金(61975017,61905015)

Application of intravascular optical coherence tomography in detection of coronary atherosclerotic plaque

QIU Yao-yang, GUI Jia-hui, HUANG Lin, HU Xue-qiang, LI Qin*   

  1. School of Life Science, Beijing Institute of Technology, Beijing 100081, China
  • Received:2021-12-30 Revised:2022-01-09 Online:2022-03-05 Published:2022-03-04
  • Contact: * liqin@bit.edu.cn

摘要: 血管内光学相干层析成像(IVOCT)技术近年来在冠状动脉粥样硬化斑块检测方面发展非常迅速,可实现血管内病变组织高分辨率、无辐射、实时在体成像,在临床诊断方面发挥了重要的作用。本文简要介绍了IVOCT的成像原理、生物组织光学特征参数以及色散系数的计算方法,并对动脉粥样硬化斑块的机器学习算法进行了概述,为构建斑块的智能识别系统提供了研究思路。

关键词: 血管内光学相干层析成像, 动脉粥样硬化斑块, 斑块识别, 光学特征参数, 机器学习

Abstract: Intravascular optical coherence tomography (IVOCT) technology has developed very rapidly in the detection of coronary atherosclerotic plaque in recent years. It can realize high-resolution, radiation-free and real-time in vivo imaging of intravascular diseased tissue, and plays an important role in clinical diagnosis. This paper briefly introduces the imaging principle of IVOCT, calculation methods of the optical characteristic parameters of biological tissue and the dispersion coefficient. The plaque recognition algorithm based on machine learning is also briefly summarized, so as to provide a new strategy and pathway for the development of constructing the artificial intelligent recognition system of plaque.

Key words: intravascular optical coherence tomography, atherosclerotic plaque, plaque recognition, optical characteristic parameters, machine learning

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