人工智能在白内障诊断的应用进展OA
Advances in artificial intelligence for cataract diagnosis
白内障是世界范围内致盲的主要原因之一,占中低收入国家致盲病例的50%.随着人口老龄化程度的加深,到2050年中国白内障致盲病例预计达到2 000万.卫生支出占比低、医疗设备及眼科医生紧缺、筛查费用昂贵仍是中低收入国家无法开展大规模白内障筛查的主要原因.人工智能(artificial intelligence,AI)协助白内障诊断具有便捷、低成本、可远程进行等优点,有望减少甚至避免白内障致盲的发生.文章将对AI通过结合裂隙灯眼前节图像、眼底照片及扫频源光学相干层析图像进行白内障自动诊断等研究进行简要综述.
Cataract is a primary cause of blindness globally,particularly accounting for 50%of blindness cases in low-and middle-income countries.As the population ages,it is predicated that cataract blindness cases in China will rise to 20 million by 2050.However,low health expenditures,scarcity of medical equipment and ophthalmologists,and high screening costs continue to hinder mass cataract screening in these countries.Artificial intelligence(AI)-assisted cataract diagnosis offers significant advantages,including convenience,cost-effectiveness,and remote accessibility,potentially reducing or even eliminating cataract blindness.This review aims to concisely summarize the research on automatic cataract diagnosis utilizing AI,incorporating slit lamp images of anterior eye segment,fundus photographs,and swept source optical coherence tomography images.
颜钰玲;薛春燕
中国人民解放军总医院海南医院眼科,三亚 572013||南京大学医学院,南京 210000中国人民解放军总医院海南医院眼科,三亚 572013
计算机与自动化
人工智能白内障裂隙灯眼前节图像眼底照片扫频源光学相干层析图像
artificial intelligencecataractslit lamp images of anterior eye segmentfundus imagesswept source optical coherence tomography images
《眼科学报》 2024 (003)
160-168 / 9
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