Zahmatkesh, M., Rafiee, A., Mazinani, M. (2013). Intelligent Diabetic Retinopathy Diagnosis in Retinal Images. Journal of Advances in Computer Research, 4(3), 103-117.
Marzie Zahmatkesh; Ali Rafiee; Majid Mazinani. "Intelligent Diabetic Retinopathy Diagnosis in Retinal Images". Journal of Advances in Computer Research, 4, 3, 2013, 103-117.
Zahmatkesh, M., Rafiee, A., Mazinani, M. (2013). 'Intelligent Diabetic Retinopathy Diagnosis in Retinal Images', Journal of Advances in Computer Research, 4(3), pp. 103-117.
Zahmatkesh, M., Rafiee, A., Mazinani, M. Intelligent Diabetic Retinopathy Diagnosis in Retinal Images. Journal of Advances in Computer Research, 2013; 4(3): 103-117.
Intelligent Diabetic Retinopathy Diagnosis in Retinal Images
1Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Khorasan Razavi, Neyshabur, Iran
2Department of Electrical Engineering, Islamic Azad University, Kazeroun Branch, Kazeroun, Iran
3Department of Electrical Engineering, Emam Reza University, Mashhad, Iran
Abstract
Diabetic Retinopathy is one of the most important reasons of blindness which causes serious damage in the retina. The aim of this research is to detect one lesions of the retina, named Exudates automatically with Image processing techniques. Preprocessing is the first step of proposed algorithm. After preprocessing, the optic disc was detected and removed from the retinal image due to the same color of OD and the exudates. Next, the HSV format of image has been used where the H and V channels, standard deviation on green channel of retinal image and the background removal features were used as input of the system. The Fuzzy C-mean algorithm is used for classification. In this research the databases were Diaretdb0 and Diaretdb1. The results show 88.86% for Sensitivity and 99.98% for Specificity. Also, the result for PPV was 95.66% and the Accuracy was 99.90%.
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