Classification of diabetic retinopathy using artificial neural network
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Creator 1. Weeragul Pratumgul
2. Worawat Sa-ngiamwibool
Title Classification of diabetic retinopathy using artificial neural network
Publisher Faculty of Engineering, Khon Kaen University
Publication Year 2559
Journal Title KKU Engineering Journal
Journal Vol. 43
Journal No. S1
Page no. 74-77
Keyword Diabetic retinopathy, Artificial neural network, Image processing, Telemedicine
ISSN 0125-8273
Abstract Diabetic retinopathy (DR) is one of the complications caused by diabetes which shows abnormalities symptoms in retinopathy and is a major cause of loss of vision. The screening by an ophthalmologist is the only way to prevent this problem. This work, aim to develop classification of diabetic retinopathy algorithm by using Artificial Neural Network (ANN) for work together with telemedicine project in Thailand. First, using mathematic morphology and image processing techniques to extract features that are factor of DR. Then, input into ANN to grading the symptoms of DR. When comparing the performance of proposed software with diagnosis of ophthalmologist found that, its diagnosis have accuracy of 98.89%, sensitivity of 99.26%, specificity of 97.77% and positive predictive values at 99.26%. Thus, proposed software can helps to increase occasion of screening diabetes patients, especially in remote area where lack of ophthalmologists or specialist to read fundus images. Suitable for telemedicine system. Moreover, also can improve accuracy of ophthalmologists's diagnosis.
KKU Engineering Journal

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