随着人工智能(artificial intelligence，AI)技术的快速发展，基于深度学习(deep learning，DL)和机器学习的AI技术在医学领域上的应用受到了广泛的关注。AI在眼科的应用也逐渐向更全面更深入的层次发展，通过角膜断层扫描、光学相干断层扫描、裂隙灯图像等技术，AI在对角膜病变、结膜病变、白内障、青光眼等眼部疾病的诊断和治疗方面都表现出了良好的性能。然而AI在眼科的应用方面也存在一些诸如结果可解释性的欠缺、数据集标准化的缺乏、数据集质量的不齐、模型适用性的不足和伦理问题等挑战。在5G和远程医疗飞速发展的时代，眼科AI同时也有许多新的机遇。本文综述了AI在前段眼科疾病中的应用、临床实施的潜在挑战和前景，为AI在眼科领域的进一步发展提供参考信息。

With the rapid development of artificial intelligence (AI) technology, the application of AI technology based on deep learning (DL) and machine learning (ML) in the medical field has received widespread attention. The application of AI in ophthalmology is gradually being shifted to a more comprehensive and in-depth level. Trained on corneal tomography, optical coherence tomography (OCT), slit-lamp images, and other techniques. AI can achieve robust performance in the diagnosis and treatment of corneal lesions, conjunctival lesions, cataract, glaucoma and other ophthalmic diseases. However, there are also some challenges in the application of AI in ophthalmology, including the lack of interpretability of results, lack of standardization of data sets, uneven quality of data sets, insufficient applicability of models and ethical issues. In the era of 5G and telemedicine, there are also many new opportunities for ophthalmic AI. In this review, we provided a summary of the state-of-the-art AI application in anterior segment ophthalmic diseases, potential challenges in clinical implementation and its development prospects, and provides reference information for the further development of artificial intelligence in the field of ophthalmology.

光学相干断层扫描血管成像术(optical coherence tomography angiography，OCTA)作为一项新兴的检查手段，现已被广泛应用于眼科临床及科研工作中。鉴于OCTA在血管成像方面的独特优势，近年来关于其在眼前段的临床应用和研究也愈发得到关注。关于OCTA对结膜、巩膜、角膜以及虹膜的血管和相关眼表疾病的研究日益增多，其在眼前段应用潜力巨大。

As a new examination method, optical coherence tomography angiography (OCTA) has been increasingly used in ophthalmology clinical work and scientific research. In view of the unique advantages of OCTA in angiography,the clinical application and research of OCTA in the anterior segment have attracted more and more attention in recent years. Studies of OCTA in vessels of conjunctiva, sclera, cornea, iris, and related ocular surface diseases have shown great potential for its application in the anterior segment.

目的：获取眼表图像的综合信息，建立眼表疾病综合诊断和评估。方法：将超高分辨率光学相干断层成像仪(ultra-high resolution optical coherence tomography，UHR-OCT)与基于裂隙灯生物显微镜的微血管成像系统相结合，开发了一种多模态、非接触式的眼科光学成像平台。结果：UHR-OCT模块在组织中实现轴向分辨率约为2 μm 。眼表微血管成像模块在最大放大倍率下横向分辨率约为3.5 μm。通过集成在裂隙灯显微镜成像光学路径的不同模块，多模态成像平台能够执行实时前段OCT结构成像、结膜微血管成像和传统裂隙灯成像功能。利用自主开发的软件，进一步分析结膜血管网络图像和血流图像，获取血管分形维数、血流速度、血管直径等定量形态学和血流动力学参数。结论：通过在健康受试者和角膜炎患者的在体成像测试，表明多模态眼前段成像设备可为眼科临床应用及人工智能提供结构和功能信息数据。

Objective: To obtain the comprehensive information of the anterior eye image, establish complementary information for the diagnosis and evaluation of ocular diseases. Methods: We developed a multi-modal, non-invasive optical imaging platform by combining ultra-high resolution optical coherence tomography (UHR-OCT) with a microvascular imaging system based on slit-lamp biomicroscopy. Results: The uHR-OCT module achieved an axial resolution of approximately 2 μm in tissues. The lateral resolution of the ocular surface microvascular imaging module under maximum magnification was approximately 3.5 μm. By combining the imaging optical paths of different modules, the customized multi-modal eye imaging platform was capable of performing real-time cross-sectional UHR-OCT imaging of the anterior eye, conjunctival vessel network imaging, high-resolution conjunctival blood flow videography, and traditional slit-lamp imaging on a single device. With self-developed software, a conjunctival vessel network image and blood flow videography were further analyzed to acquire quantitative morphological and hemodynamics parameters, including vessel fractal dimensions, blood flow velocity and vessel diameters. Conclusion: The ability of the multi-modal anterior eye imager to provide both structural and functional information for ophthalmic clinical applications can be demonstrated in a healthy human subject and a keratitis patient.