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OA

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.