人工智能在白内障诊断领域的应用进展
The application progress of artificial intelligence in cataract diagnosis
谢家兴 1李学民 2敖明昕2
作者信息
- 1. 100191 北京大学医学部
- 2. 100191 北京大学第三医院眼科 眼部神经损伤的重建保护与康复北京市重点实验室
- 折叠
摘要
近年来,伴随社会人口老龄化进程白内障的患病率不断攀升.为缓解医疗资源配置的不足,基于裂隙灯显微镜图像、彩色眼底图像以及相干光断层扫描图像的人工智能白内障辅助诊断技术在白内障筛查和分级诊断中发挥了应用效能.其中,经典的机器学习算法依据特征被应用于图像分类,通过集成学习或融合特征的方法可综合图像信息提升分类性能,深度学习算法可自动从原始图像中提取隐含特征.目前,人工智能技术已基本具备了对白内障的规模化筛查与诊断能力.本文中笔者就近年来人工智能在白内障诊断领域的应用进展进行综述.
Abstract
In recent years,with the aging of the population,the incidence of cataracts has been continuously increasing.To alleviate the shortage of medical resource allocation,artificial intelligence cataract assisted diagnosis technology based on slit lamp microscopy images,color fundus images,and coherent light tomography images has played an application role in cataract screening and grading diagnosis.Among them,classic machine learning algorithms are applied to image classification based on features.By integrating learning or fusing features,classification performance can be improved by integrating image information.Deep learning algorithms can automatically extract hidden features from the original image.At present,artificial intelligence technology has basically had the capability of screening and diagnosis for cataracts on a large scale.The application progress of artificial intelligence in the field of cataract diagnosis in recent years was reviewed in this paper.
关键词
白内障/人工智能/深度学习/裂隙灯显微镜图像/眼底图像Key words
Cataract/Artificial intelligence/Deep learning/Anterior segment image/Fundus image引用本文复制引用
出版年
2023
NETL
NSTL
万方数据