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H. Faouzi
Sultan Moulay Slimane University
Computer Science & IT Engineering

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Automatic Exudates Detection in Diabetic Retinopathy Images H. Faouzi; Mohamed Fakir
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 5, No 2: June 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (509.133 KB) | DOI: 10.11591/ijai.v5.i2.pp45-54

Abstract

Diabetic Retinopathy (DR) refers to the presence of typical retinal micro vascular lesions in persons with diabetics. When the disease is at the early state, a prompt diagnosis may help in preventing irreversible damages to the diabetic eye. If the exudates are closer to macula, then the situation is critical. Early detection can potentially reduce the risk of blind.  This paper proposes tool for the early detection of Diabetic Retinopathy using edge detection, algorithm kmeans in segmentation phase, invariant moments (Hu and Affine) and descriptor GIST in extraction phase. In the recognition phase, neural network is adopted. All tests are applied on database DIARETDB1.
Co-Authors Mohamed Fakir