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Detection of Glaucoma using image processing techniques: A review

机译：使用图像处理技术检测青光眼：综述

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This paper presents a succinct of different types of image processing methods employed for the detection of Glaucoma, most lethal eye disease. Glaucoma affects the optic nerve as a consequence of which loss of ganglia cells in retina of the eye come about and this loss eventually leads to loss of vision. The principal cause of it is increased intraocular pressure which scathes the optic nerve. There are two main types of Glaucoma, open angle and angle closure glaucoma which are responsible for increase in intraocular pressure. In the early stages of glaucoma no perceptible symptoms appears. As the disease progresses, vision starts becomes hazy and afterwards leads to the loss of vision. Therefore, early detection of glaucoma is needed to prevent loss of vision. Manual analysis of ophthalmic images is time consuming and accuracy depends on the expertise of the professionals. Automatic analysis of retinal images is becoming an important tool nowadays. Automation aids in detection, diagnosis and prevention of risks associated with the disease. Fundus images obtained from fundus camera have been used for the analysis. The techniques mentioned in the present review has certain advantages and disadvantages. Based on this study, one can easily determine which technique provides optimum result.
机译：本文介绍了用于检测青光眼，大多数致命眼部疾病的不同类型的图像处理方法。青光眼由于眼睛视网膜中的神经节细胞失去而导致的眼神肿来影响视神经，并且这种损失最终导致视力丧失。它的主要原因是增加视神经的眼内压力。青光眼具有两种主要类型，开放角度和角度闭合青光眼，这些青光眼负责人工压力的增加。在青光眼的早期阶段，出现没有可感知的症状。随着疾病的进展，愿景开始变得朦胧，之后导致视力丧失。因此，需要早期检测青光眼以防止失去视力。手工分析眼科图像是耗时，准确性取决于专业人士的专业知识。视网膜图像的自动分析正在成为现在成为一个重要的工具。自动化艾滋病检测，诊断和预防与疾病相关的风险。从眼底摄像机获得的眼底图像已用于分析。本综述中提到的技术具有一定的优缺点。基于这项研究，可以轻松确定哪种技术提供最佳结果。

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