The speedy development of digital imaging and computer vision has extended the potential of using these technologies in ophthalmology. Image processing systems are increasingly prominent in medical diagnostic systems and especially to modern ophthalmology. The retinal images give information about the health of the visual system. Retinal diseases, such as glaucoma, diabetic retinopathy, age-related macular degeneration, and many other diseases that can lead to blindness, manifest themselves in the retina. An automated system offers standardized large-scale screening at a lower cost, reduces human errors, and provides services to remote areas. Extensive research has been done since the last two decades in developing automated methods. Due to the fast evolution of new techniques, a comprehensive review is needed on such technique and algorithms present to date. This survey paper provides the reader a comprehensive review of the existing research in automated retinal image analysis. In this paper, automated computer aided methods used to diagnose retinal diseases have been reviewed. Several state-of-the art techniques and algorithms used to localize and segment features, such as optic disc and optic cup, macula and fovea, retinal blood vessels, detection of retinal lesions (microaneurysms, haemorrhages, exudates), are discussed and presented.

数字成像和计算机视觉的迅速发展扩展了在眼科学中使用这些技术的潜力。图像处理系统在医学诊断系统中，尤其是在现代眼科领域中日益突出。视网膜图像提供有关视觉系统健康的信息。视网膜疾病，例如青光眼，糖尿病性视网膜病，与年龄有关的黄斑变性和许多其他可能导致失明的疾病，都表现在视网膜中。自动化系统以较低的成本提供标准化的大规模筛查，减少了人为错误，并为偏远地区提供服务。最近二十年来，在开发自动化方法方面已经进行了广泛的研究。由于新技术的迅速发展，迄今为止，需要对这种技术和算法进行全面的审查。这份调查报告为读者提供了对自动化视网膜图像分析的现有研究的全面综述。在本文中，已经对用于诊断视网膜疾病的自动计算机辅助方法进行了综述。讨论并介绍了几种用于定位和分割特征的最新技术和算法，例如视盘和视杯，黄斑和中央凹，视网膜血管，视网膜病变（微动脉瘤，出血，渗出液）的检测。