An Effective Approach to Detect Lesions in Color Retinal Images

Diabetic-related eye diseases are the most common cause of blindness in the world. So far the most effective treatment for these eye diseases is early detection through regular screenings. To lower the cost of such screenings, we employ state-of-the-art image processing techniques to automatically detect the presence of abnormalities in the retinal images obtained during the screenings. In this paper, we focus on one of the abnormal signs: the presence of exudates/lesions in the retinal images. We propose a novel approach that combines brightness adjustment procedure with statistical classification method and local-window-based verification strategy. Experimental results indicate that we are able to achieve 100% accuracy in terms of identifying all the retinal images with exudates while maintaining a 70% accuracy in correctly classifying the truly normal retinal imagesas normal. This translates to a huge amount of savings in terms of the number of retinal images that need to be manual...

• Type: Conference
• Year: 2000
• Where: CVPR
• Authors: Huan Wang, Wynne Hsu, Kheng Guan Goh, Mong-Li Lee
• Keywords: CVPR 2000, Eye Diseases, Normal Retinal Imagesas, Retinal Images