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Detection of Exudates in Retinal Images Based on Computational Intelligence Approach


R.Sri Ranjini, M.Devaki


Vol. 13  No. 2  pp. 86-89


Currently, there is an increasing interest for setting up medical systems that can screen a large number of people for sight threatening diseases, such as diabetic retinopathy. This automated identification of exudates pathologies in retinal images based on computational-intelligence approach are used to find the diabetics. In which the color retinal images are segmented using fuzzy c means clustering algorithm which following some pre processing step and that segmented regions are divided into exudates and non exudates. The selected feature vectors are then classified using a multilayer neural network classifier to determine whether the image is abnormal/normal.


Fuzzy c-means (FCMs), Gabor filters, neural networks, retinal exudates, thresolding