中国脑血管病杂志2026，Vol.23Issue(8)：560-570,11.DOI:10.3969/j.issn.1672-5921.2026.08.007
人工智能在急性缺血性卒中多模态CT病灶识别与分割中的应用研究进展
Advances in the application of artificial intelligence for multimodal CT-based lesion identification and segmentation in acute ischemic stroke
摘要
Abstract
Acute ischemic stroke(AIS)presents with sudden onset and carries a high risk of disability and mortality.Multimodal CT,including non-contrast CT(NCCT),CT perfusion(CTP),and CT angiography(CTA),is the most widely used imaging approach for emergency AIS evaluation.However,these modalities have inherent limitations:NCCT has limited sensitivity for early ischemic lesions,CTP-derived quantitative parameters are affected by threshold selection and postprocessing variability,and CTA has relatively low accuracy for detecting medium-to-distal vascular occlusions.In recent years,artificial intelligence(AI)models based on these CT modalities have shown potential advantages over conventional methods or human interpretation in lesion identification and segmentation.This review summarized advances in AI-based lesion identification and segmentation using NCCT,CTP,and CTA in AIS,aiming to provide a reference for the translational application of AI in AIS imaging diagnosis.关键词
急性缺血性卒中/人工智能/CT/病灶检测/病灶分割/综述Key words
Acute ischemic stroke/Artificial intelligence/CT/Lesion identification/Lesion segmentation/Review引用本文复制引用
张人元,沈文卓,梁雨昕,赵晓静,张苗,卢洁..人工智能在急性缺血性卒中多模态CT病灶识别与分割中的应用研究进展[J].中国脑血管病杂志,2026,23(8):560-570,11.基金项目
首都医科大学宣武医院汇智人才项目(HZ2021ZCLJ005) （HZ2021ZCLJ005）
