IPASJ INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY (IIJIT)

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Automated Glaucoma Detection from Fundus Images using Clustering and Ellipse-Fitting, Authors : Asmita Sarkar, Soumya Kanta Sarkar, Akash Nag,IPASJ INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY (IIJIT) ,www.ipasj.org/IIJIT/IIJIT.htm

Volume & Issue no: Volume 6, Issue 4, April 2018


Title:
Automated Glaucoma Detection from Fundus Images using Clustering and Ellipse-Fitting
Author Name:
Asmita Sarkar, Soumya Kanta Sarkar, Akash Nag
Abstract:
ABSTRACT Glaucoma is one of the leading causes of blindness across the world and early diagnosis is crucial for preventing progression of the disease. In this paper, we examine how glaucoma detection can be automated by analyzing the optic-cup to disc ratio (CDR) in retinal fundus images. We have applied the K-Medians clustering algorithm to automatically determine the cup and disc regions, followed by fitting an ellipse to compute the CDR. The CDR is then checked against a threshold value to determine whether or not the patient is suffering from glaucoma. We have applied our algorithm to test 455 fundus images from a standard set of normal and glaucomatous images, and have achieved an accuracy of 61%. Keywords: glaucoma, CDR, k-medians, clustering, ellipse-fitting
Cite this article:
Asmita Sarkar, Soumya Kanta Sarkar, Akash Nag , " Automated Glaucoma Detection from Fundus Images using Clustering and Ellipse-Fitting " , IPASJ INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY (IIJIT), Volume 6, Issue 4, April 2018 , pp. 001-005 , ISSN 2321-5976.
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