A Review on the optic disc and optic cup segmentation and classification approaches over retinal fundus images for detec
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A Review on the optic disc and optic cup segmentation and classification approaches over retinal fundus images for detection of glaucoma H N Veena1 · A Muruganandham2 · T Senthil Kumaran1 Received: 28 August 2019 / Accepted: 16 July 2020 © Springer Nature Switzerland AG 2020
Abstract 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. Keywords Intraocular pressure (IOP) · Optic disc (OD) · Optic cup (OC) · Optic nerve head (ONH) · Convolutional neural network (CNN)
1 Introduction
1.1 Retinal fundus images
Medical imaging is a process of creating images of internal parts of the human body for medical diagnosis. The internal structure of the body can be easily visualized with medical images. Many recordings and measurement techniques are used to produce images. Computer vision techniques and medical analysis concepts are designed to provide medical image data. It is extended to all fields of medical science, especially to Ophthalmology. Ophthalmology [1] is a medical branch in which it deals with diagnosis and treatment of eye disorder. There are many retinal diseases, such as glaucoma, diabetic retinopathy, cataracts, etc. From the past 15 years, various techniques for the automatic detection of glaucoma are developed but these methods need an improvement.
The human eye is an essential organ in the human body in which allows vision. The human eye is capable to differentiate more than 10 million colors, enables depth perception. It is composed of two segments, namely the anterior segment and the posterior segment. The anterior segment consists of iris, cornea, and lens. The posterior segments composed of retina, vitreous, choroid, and sclera. The area where the connection between sclera and cornea is the limbus. The central part of the eye is called the pupil and which is surrounded by a pigmented circular area called iris. Figure 1 [2] shows the anatomical structure of the human eye. The fundus camera is used to capture the retinal images, and these images are called fundus images. These images help doctors to quickly diagnose most varieties of
* H N Veena, [email protected] | 1Department of Computer Science and Engineering, ACS College
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