NDLI: Automated Diagnosis of Glaucoma Using Digital Fundus Images

Content Provider	Springer Nature Link
Author	Nayak, Jagadish Acharya U., Rajendra Bhat, P. Subbanna Shetty, Nakul Lim, Teik Cheng
Copyright Year	2008
Abstract	Glaucoma is a disease of the optic nerve caused by the increase in the intraocular pressure of the eye. Glaucoma mainly affects the optic disc by increasing the cup size. It can lead to the blindness if it is not detected and treated in proper time. The detection of glaucoma through Optical Coherence Tomography (OCT) and Heidelberg Retinal Tomography (HRT) is very expensive. This paper presents a novel method for glaucoma detection using digital fundus images. Digital image processing techniques, such as preprocessing, morphological operations and thresholding, are widely used for the automatic detection of optic disc, blood vessels and computation of the features. We have extracted features such as cup to disc (c/d) ratio, ratio of the distance between optic disc center and optic nerve head to diameter of the optic disc, and the ratio of blood vessels area in inferior-superior side to area of blood vessel in the nasal-temporal side. These features are validated by classifying the normal and glaucoma images using neural network classifier. The results presented in this paper indicate that the features are clinically significant in the detection of glaucoma. Our system is able to classify the glaucoma automatically with a sensitivity and specificity of 100% and 80% respectively.
Starting Page	337
Ending Page	346
Page Count	10
File Format	PDF
ISSN	01485598
Journal	Journal of Medical Systems
Volume Number	33
Issue Number	5
e-ISSN	1573689X
Language	English
Publisher	Springer US
Publisher Date	2008-08-09
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Glaucoma Eye Fundus Image processing Neural network Health Informatics Statistics for Life Sciences, Medicine, Health Sciences
Content Type	Text
Resource Type	Article
Subject	Health Information Management Information Systems Health Informatics

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