中医眼耳鼻喉杂志2026，Vol.16Issue(1)：37-40,4.DOI:10.3969/j.issn.1674-9006.2026.01.010
人工智能在识别及分析糖尿病视网膜病变OCTA图像中视网膜无灌注区的研究进展
Research progress of artificial intelligence in analyzing the retinal non-perfusion area in OCTA images of diabetic retinopathy
刘信志 1钟捷 2秦雅雯 2李杰2
作者信息
- 1. 610075,四川成都,成都中医药大学
- 2. 610072,四川成都,四川省人民医院
- 折叠
摘要
Abstract
Diabetes Mellitus(DM)is a significant challenge in global public health,with its epidemiological charac-teristics showing a marked upward trend.Diabetic retinopathy(DR),a major blinding complication of diabetes,has non-perfusion area(NP)as a key indicator reflecting its severity.Optical coherence tomography angiography(OCTA),a non-invasive and high-resolution vascular imaging technique,has a significant advantage in displaying NP.In recent years,ar-tificial intelligence(AI)technology,especially deep learning,has become a powerful tool for analyzing OCTA images,en-abling automatic recognition and quantitative analysis of NP.This article reviews the technical methods,performance,clinical applications,and challenges of using AI to analyze NP in OCTA images of DR patients,with the aim of providing references for related research and clinical applications.关键词
糖尿病视网膜病变/视网膜无灌注区/人工智能/OCTAKey words
Diabetic retinopathy/Retinal non-perfusion Area/Artificial intelligence/OCTA分类
医药卫生引用本文复制引用
刘信志,钟捷,秦雅雯,李杰..人工智能在识别及分析糖尿病视网膜病变OCTA图像中视网膜无灌注区的研究进展[J].中医眼耳鼻喉杂志,2026,16(1):37-40,4.
