Department of Biomedical Engineering, National University of Singapore, Singapore, Singapore.
Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore.
Br J Ophthalmol. 2020 Mar;104(3):301-311. doi: 10.1136/bjophthalmol-2019-315016. Epub 2019 Oct 22.
Glaucoma is a result of irreversible damage to the retinal ganglion cells. While an early intervention could minimise the risk of vision loss in glaucoma, its asymptomatic nature makes it difficult to diagnose until a late stage. The diagnosis of glaucoma is a complicated and expensive effort that is heavily dependent on the experience and expertise of a clinician. The application of artificial intelligence (AI) algorithms in ophthalmology has improved our understanding of many retinal, macular, choroidal and corneal pathologies. With the advent of deep learning, a number of tools for the classification, segmentation and enhancement of ocular images have been developed. Over the years, several AI techniques have been proposed to help detect glaucoma by analysis of functional and/or structural evaluations of the eye. Moreover, the use of AI has also been explored to improve the reliability of ascribing disease prognosis. This review summarises the role of AI in the diagnosis and prognosis of glaucoma, discusses the advantages and challenges of using AI systems in clinics and predicts likely areas of future progress.
青光眼是视网膜神经节细胞不可逆转损伤的结果。虽然早期干预可以最大限度地降低青光眼致盲的风险，但由于其无症状，因此很难在晚期之前进行诊断。青光眼的诊断是一项复杂且昂贵的工作，严重依赖于临床医生的经验和专业知识。人工智能（AI）算法在眼科学中的应用提高了我们对许多视网膜、黄斑、脉络膜和角膜病变的认识。随着深度学习的出现，已经开发出了许多用于眼部图像分类、分割和增强的工具。多年来，已经提出了几种 AI 技术来帮助通过对眼睛的功能和/或结构评估来检测青光眼。此外，还探索了使用 AI 来提高疾病预后归因的可靠性。本综述总结了 AI 在青光眼诊断和预后中的作用，讨论了在临床中使用 AI 系统的优势和挑战，并预测了未来可能的进展领域。
