基于青光眼影像的人工智能辅助诊断技术及进展  

Artificial Intelligence-Assisted Diagnosis Technology and Its Advance Based on Glaucoma Imaging

作　　者：李明远[1] 房丰洲[1] Li Mingyuan;Fang Fengzhou(Laboratory of Micro/Nano Manufacturing Technology,State Key Laboratory of Precision Measuring Technology and Instruments,Tianjin University,Tianjin 300072,China)

机构地区：[1]天津大学精密测试技术及仪器全国重点实验室,微纳制造实验室,天津300072

出　　处：《激光与光电子学进展》2024年第14期9-20,共12页Laser & Optoelectronics Progress

基　　金：国家自然科学基金(52035009)。

摘　　要：人眼内异常的眼内压是青光眼的主要表现之一,而在疾病的早期阶段患者并没有感到明显不适,往往难以及时发现,如果该疾病未得到及时治疗,则可能导致完全失明。青光眼的早期诊断可以有效预防永久性视力丧失,临床上人工检查是一种可行的解决方案,但这不仅费时费力,而且要求医生具备专门的知识和经验。现有的研究成果表明,将人工智能技术整合到影像中预防和检测青光眼是高效、准确的。系统介绍基于人工智能的青光眼辅助诊断领域的最新进展,探讨各种已发表的算法模型,总结此类研究存在的问题及未来可能的研究方向,并对基于多模态评估的青光眼智能检测技术的研究现状与未来发展趋势进行详细和深入的评述。Abnormal intraocular pressure within the human eye is one of the main manifestations of glaucoma.In the early stages of the disease,patients often do not experience significant discomfort,making it difficult to be aware in a timely manner.If the condition is not treated promptly,it may lead to complete blindness.Early diagnosis of glaucoma can effectively prevent permanent vision loss.Clinical manual examinations are a viable solution,but they are not only timeconsuming and laborintensive but also require doctors to possess specialized knowledge and experience.Existing research results indicate that integrating artificial intelligence technology into imaging for the prevention and detection of glaucoma is efficient and accurate.This article systematically introduces the latest developments in the field of glaucoma auxiliary diagnosis based on artificial intelligence,discusses various published algorithm models,summarizes the challenges in such research,and outlines possible future research directions.It provides a comprehensive and indepth review of the current research status and future development trends in intelligent glaucoma detection technology based on multimodal assessment.

关 键 词：青光眼 深度学习 人工智能 光学相干断层扫描 眼底图像 视野 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]