青光眼是全球不可逆性失明的主要原因,其特征是视神经乳头凹陷和视野损伤。慢性青光眼通常无痛,典型的视野缺损多出现在晚期。该疾病主要影响视神经,如不及时干预,可能会导致失明。因此,早期检测和治疗对于保护患者视力至关重要。随着数字成像技术的进步,如眼底照相机和扫描激光检眼镜(Scanning Laser Ophthalmoscopes, SLO),眼科专业人员能够更有效地识别青光眼。近年来,人工智能(Artificial Intelligence, AI)在医学领域迅速发展,在提升青光眼筛查效率和降低成本方面展现了巨大潜力。本文回顾了基于人工智能的彩色眼底照相技术在青光眼筛查中的最新技术进展,探讨了当前临床实施中的挑战与发展方向。Glaucoma is the leading cause of irreversible blindness worldwide, characterized by optic nerve head cupping and visual field damage. Chronic forms of glaucoma are often painless, with symptomatic visual field defects appearing only in later stages. The disease primarily affects the optic disc, and without timely intervention, it can progressively lead to blindness. Therefore, early detection and treatment are critical to preserving patients’ vision. Advances in digital imaging technologies, such as fundus cameras and Scanning Laser Ophthalmoscopes (SLO), have enabled eye care professionals to identify glaucoma more effectively. In recent years, Artificial Intelligence (AI) has rapidly evolved in the medical field, offering significant potential to enhance glaucoma screening efficiency and reduce costs. This article reviews the latest technological advancements in AI-driven color fundus photography for glaucoma screening, discusses current challenges and future directions in clinical implementation.
