Paper Title :Computer Aided Automatic Glaucoma Diagnosis
Author :Priya Kumbhare, Manisha Turkar, Rashmi Kularkar
Article Citation :Priya Kumbhare ,Manisha Turkar ,Rashmi Kularkar ,
(2014 ) " Computer Aided Automatic Glaucoma Diagnosis " ,
International Journal of Electrical, Electronics and Data Communication (IJEEDC) ,
pp. 28-32,
Volume-2,Issue-2
Abstract : Abstract— This paper proposes the novel method for detection of glaucoma which is second leading cause of blindness
worldwide Glaucoma is a group of diseases of the optic nerve involving loss of retinal ganglion cells. This is caused by
increased pressure of fluid in the eye. This can result in decreased peripheral vision and, eventually, blindness. Untreated
Glaucoma leads to permanent damage of the optic nerve and resultant visual field loss, which can progress to blindness. In
this paper we use a combination of texture and higher order spectrum (HOS) features for detection of glaucoma from digital
fundus images. The texture features include the co-ocurrence matrix and run length matrix based features. Minimum
distance classifier and naïve bayes classifier are used to perform supervised classification \. The navie bayes classifier is
found to be more accurate than the minimum distance classifier. Also the detection of glaucoma using HOS features is found
to be more accurate than the textures features. Our proposed novel features are clinically significant and can be used to
detect glaucoma accurately. Our project will be useful in easy and low cost detection of glaucoma so that it can be treated
easily. Our goal is to develop an auto diagnostic system that will support the medical examination for finding glaucoma.
Type : Research paper
Published : Volume-2,Issue-2
DOIONLINE NO - IJEEDC-IRAJ-DOIONLINE-482
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Published on 2014-03-03 |
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