Classification and Identification of Diabetic Retinopathy Severity Stages in Thai Patients Using Deep Learning Based Convolution Neural Networks
Diabetic retinopathy (DR) is one of the complications caused by long term diabetes, which has an effect on vision quality of the patient leading eventually to permanent vision loss. This research has developed an automated method for screening and identifying the severity of diabetic retinopathy in Thai patients by using image processing principles together with a Deep Learning (DL) technique based Convolution Neural Network (CNN) The purposed method was used to learn from 9,900 color fundus retinal images and tested with 3,300 sets of DR images. The results showed 99.36% accuracy level and 99.48% of sensitivity level when compared with the diagnosis made by an ophthalmologist.