A Review on the optic disc and optic cup segmentation and classification approaches over retinal fundus images for detection of glaucoma

被引：0

作者：

H N Veena

A Muruganandham

T Senthil Kumaran

机构：

[1] VTU,Department of Computer Science and Engineering, ACS College of Engineering

[2] VTU,Electronics and Communication Engineering, Raja Rajeswari College of Engineering

来源：

SN Applied Sciences | 2020年 / 2卷

关键词：

Intraocular pressure (IOP); Optic disc (OD); Optic cup (OC); Optic nerve head (ONH); Convolutional neural network (CNN);

D O I：

暂无

中图分类号：

学科分类号：

摘要：

Glaucoma is one of the leading severe retinal disease which damages the optic nerve head on the retinal part of the eye irreversibly. Once the person is diagnosed with glaucoma, it cannot be treated entirely, but it can be controlled. If glaucoma is not diagnosed in time, it will lead to vision loss by damaging the Optic Nerve Head. The glaucoma detection is performed based on the optic disc and optic cup parameters on the retinal part of the eye. In the existing system, many image processing and machine learning techniques used for the segmentation and classification of optic disc and optic cup. To improve the precision of diagnosis, the existing techniques used need an improvement. This article helps readers with more information about the existing methods applied for the diagnosis of glaucoma, it also lists the research gaps and technical challenges to improve the accuracy of segmentation and classification methods.

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