a novel technique to detect macular edema based on motion patterns
Arun Kumar.S,Lakshmiprabha.N,N. Stalin
Published in International Journal of Advanced Research in Computer Science Engineering and Information Technology
ISSN: 2321-3337 Impact Factor:1.521 Volume:1 Issue:1 Year: 06 June,2013 Pages:45-54
Abstract
In this paper a two-stage methodology for the detections and classification of Diabetic Macular Edema severity from color fundus image 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 image. Disease severity is assessed using a rotational asymmetry metric by examining the symmetry of macular region. Diabetic macular edema (DME) is an advanced symptom of diabetic retinopathy and can lead to irreversible vision loss.
Kewords
Hard Exudates(HE), Diabetic Macular Edema (DME), Optic Disc (OD), Diabetic retinopathy (DR), Color Fundus Image(CFI),Region Of Interest (ROI).
Reference
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