EARLY DETECTION OF MACULAR EDEMA IN FUND

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EARLY DETECTION OF MACULAR EDEMA IN FUND

Abstract

Medical systems based on state of the art image processing and pattern recognition techniques are very common now a day. These systems are of prime interest to provide basic health care facilities to patients and support to doctors. Diabetic macular edema is one of the retinal abnormalities in which diabetic patient suffers from severe vision loss due to affected macula. It affects the central vision of the person and causes total blindness in severe cases. Dme occurs when fluid and protein deposits collect on or under the macula of the eye. These leakages cause the macula to thicken and swell, progressively distorts a persons vision. So in this article detection of exudates and its proximity towards macula determines and thereby its severity level. In this article, we propose an intelligent system for detection and grading of macular edema to assist the ophthalmologists in early and automated detection of the disease. The proposed system consists of a novel method for accurate detection of macula using a detailed feature. A two-stage methodology for the detection and classification of dme severity from color fundus images is proposed. Dme detection is carried out via a supervised learning approach using the normal fundus images. A feature extraction technique is introduced to capture the global characteristics of the fundus images and discriminate the normal

from dme images.

Author

Prof R.Jayanthi Dr.K.Bommannaraja Mrs.R.Manju

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International Journal of Advanced
Science and Engineering Research

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