国际医学放射学杂志2026，Vol.49Issue(3)：308-313,6.DOI:10.19300/j.2026.Z22222
深度学习技术在脑小血管病MRI影像特征判读中的研究进展
Advances in deep learning-based interpretation of MRI imaging features in cerebral small vessel disease
摘要
Abstract
Cerebral small vessel disease(cSVD)is a common cerebrovascular disorder,and MRI is the primary method for evaluating its imaging features.However,conventional MRI has limitations such as the lack of quantitative standards and strong subjectivity.Currently,deep learning(DL)technology provides a novel solution for the automated,quantitative,and high-precision interpretation of MRI features in cSVD.This article reviews the latest research progress of DL technology in the interpretation of MRI imaging features in cSVD,including its application in recent small subcortical infarcts,lacunes of presumed vascular origin,white matter hyperintensities,perivascular spaces,cerebral microbleeds,brain atrophy and total cSVD burden assessment,and further analyzes the current challenges and prospects.关键词
人工智能/深度学习/脑小血管病/磁共振成像Key words
Artificial intelligence/Deep learning/Cerebral small vessel disease/Magnetic resonance imaging分类
医药卫生引用本文复制引用
李锐,韩彤..深度学习技术在脑小血管病MRI影像特征判读中的研究进展[J].国际医学放射学杂志,2026,49(3):308-313,6.基金项目
天津市卫生健康科技项目高层次人才专项基金(TJWJ2024RC016) （TJWJ2024RC016）
卫生健康行业高层次人才选拔培养基金(TJSJMYXYC-D2-059.b) （TJSJMYXYC-D2-059.b）
