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山东大学学报 (医学版) ›› 2023, Vol. 61 ›› Issue (12): 1-6.doi: 10.6040/j.issn.1671-7554.0.2023.0773

• 医学影像人工智能的创新与挑战—专家综述 •    下一篇

人工智能在心肌影像应用中的研究进展

聂佩1,王锡明2,*()   

  1. 1. 青岛大学附属医院放射科, 山东 青岛 266003
    2. 山东第一医科大学附属山东省立医院医学影像科, 山东 济南 250021
  • 收稿日期:2023-08-30 出版日期:2023-12-10 发布日期:2024-01-11
  • 通讯作者: 王锡明 E-mail:wxming369@163.com
  • 作者简介:王锡明，山东第一医科大学附属省立医院医学影像中心主任/影像科主任，山东第一医科大学放射学院放射影像专业学术带头人、放射影像学系主任，山东大学/山东第一医科大学二级教授、博士研究生导师。研究方向为心脑血管疾病及胸部疾病影像诊断、医学影像人工智能。荣誉称号：国家卫生健康突出贡献中青年专家，山东省“泰山学者”特聘专家，山东省有突出贡献的中青年专家。学术任职：中华医学会放射学分会委员及分子影像学组副组长、中华医学会心血管病学分会心血管病影像学组委员、山东省医学会放射学分会候任主任委员、国家心血管病专家委员会委员、中国医师协会放射医师分会委员、山东省研究型医院协会医学影像诊断学分会主任委员
  • 基金资助:
    国家自然科学基金(82271993);中国博士后科学基金(2021M701811)

Research progress in the application of artificial intelligence in myocardial imaging

Pei NIE1,Ximing WANG2,*()   

  1. 1. Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao 266003, Shandong, China
    2. Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, Shandong, China
  • Received:2023-08-30 Online:2023-12-10 Published:2024-01-11
  • Contact: Ximing WANG E-mail:wxming369@163.com

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摘要：

近年来，人工智能(AI)在心肌影像领域展现出巨大潜力。AI算法实现了心肌影像的自动分割和测量，优化了工作流程。此外，AI通过影像组学和深度学习技术，提取能表征心肌病理改变的定量特征，辅助缺血性心肌病和非缺血性心肌病的精准诊断和预后评估。论文主要从心肌AI图像分析、影像AI辅助心肌疾病诊断和预后评估方面综述AI在心肌影像中的研究进展，并分析心肌影像AI的局限性，以期为更深入的心肌影像AI临床应用研究提供参考。

关键词: 人工智能, 心肌, 影像

Abstract:

Recently, artificial intelligence (AI) has shown great potential in myocardial imaging. AI algorithms achieve automatic segmentation and measurement of myocardial images thus optimizing the workflow. The quantitative features which characterized the pathological changes of myocardium were extracted through radiomics and deep learning techniques. These features may facilitate precise diagnosis and outcome prediction of ischemic and non-ischemic cardiomyopathies. In this review, we will introduce the research progress of AI in myocardial imaging from several aspects: AI-assisted image analysis, diagnosis and outcome evaluation of cardiomyopathies. The limitations of AI in myocardial imaging will also be discussed. We hope this review may provide references for further clinical application research of AI in myocardial imaging.

Key words: Artificial intelligence, Myocardium, Imaging

中图分类号: 

  • R816.2
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