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Analyzing Macular Edema In Diabetic Patients

Journal: International Journal of Computational Engineering Research(IJCER) (Vol.03, No. 6)

Publication Date:

Authors : ;

Page : 12-18

Keywords : Abnormality detection; diabetic macular edema; hard exudates; PCA; Neural network.;

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Abstract

Diabetic macular edema (DME) is an advanced symptom of diabetic retinopathy and can lead to irreversible vision loss. In this paper, 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. Disease severity is assessed using the neural networks.

Last modified: 2013-06-21 14:01:03