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A Novel Approach to Glaucoma Screening using Computer Vision

机译:利用计算机视觉筛查青光眼的新方法

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Glaucoma is one of the major and critical eye diseases discovered till date. It is actually a group of diseases that damage the optic nerve and subsequently result in vision loss and blindness. One of the major causes of Glaucoma is the intrinsic distortion of the optic nerve resulting in high fluid pressure on the front portion of the eye. The primary objective of the paper is to classify High Resolution Fundus images of the retina into Glaucomatous and Non-Glaucomatous. In order to achieve that, a DL-ML Hybrid Model has been developed with an initial image processing. The overall methodology followed in this paper has been termed as N-S Model. The HRF (High Resolution Fundus) Image Database consisting of 30 images is used for the purpose. The N-S Model was deployed after development and clocked a 100% Validation Accuracy and Sensitivity of 1.0. Such an Intelligent System can accelerate the process of diagnosis and reduce the review of doctors.
机译:青光眼是迄今为止发现的主要和严重的眼部疾病之一。实际上,这是一组损害视神经并随后导致视力丧失和失明的疾病。青光眼的主要原因之一是视神经的内在畸变,导致眼睛前部的高液体压力。本文的主要目的是将视网膜的高分辨率眼底图像分类为青光眼和非青光眼。为了实现这一点,已经开发了具有初始图像处理的DL-ML混合模型。本文遵循的总体方法被称为N-S模型。为此,使用了由30张图像组成的HRF(高分辨率眼底)图像数据库。 N-S模型是在开发后部署的,其验证准确度和敏感度均为100%,为1.0。这样的智能系统可以加快诊断过程,并减少对医生的检查。

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