Analyzing Macular Edema In Diabetic Patients
Journal: International Journal of Computational Engineering Research(IJCER) (Vol.03, No. 6)Publication Date: 2013-06-21
Authors : Deepika.K.G Prof.Prabhanjan.S;
Page : 12-18
Keywords : Abnormality detection; diabetic macular edema; hard exudates; PCA; Neural network.;
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.
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Last modified: 2013-06-21 14:01:03