Detection of Glaucoma Using Retinal Fundus Images

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dc.contributor.author Hafsah Ahmad
dc.contributor.author Aqsa Shakeel
dc.contributor.author Syed Omer Gillani
dc.contributor.author Umer Ansari
dc.contributor.author Abubakar Yamin
dc.date.accessioned 2017-12-26T11:24:07Z
dc.date.available 2017-12-26T11:24:07Z
dc.date.issued 2014
dc.identifier.uri http://hdl.handle.net/123456789/5186
dc.description.abstract This paper proposes an image processing technique for the detection of glaucoma which mainly affects the optic disc by increasing the cup size. During early stages it was difficult to detect Glaucoma, which is in fact second leading cause of blindness. In this paper glaucoma is categorized through extraction of features from retinal fundus images. The features include (i) Cup to Disc Ratio (CDR), which is one of the primary physiological parameter for the diagnosis of glaucoma and (ii) Ratio of Neuroretinal Rim in inferior, superior, temporal and nasal quadrants i.e. (ISNT quadrants) for verification of the ISNT rule. The novel technique is implemented on 80 retinal images and an accuracy of 97.5% is achieved taking an average computational time of 0.8141 seconds. en_US
dc.language.iso en en_US
dc.publisher Bahria University Islamabad Campus en_US
dc.subject Department of Computer Engineering CE en_US
dc.title Detection of Glaucoma Using Retinal Fundus Images en_US
dc.type Article en_US


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