Bright Lesions Detection on Retinal Images by Convolutional Neural Network

This paper is focused on automatic detection and classification of diabetic retinopathy symptoms, more specifically on the bright lesions (soft and hard exudates) as one of the primary signs suitable for diabetic retinopathy screening. We use a convolutional neural network (CNN) for bright lesions detection and evaluate achieved results using criterion based on proper comparison of each lesion with ground truth images scored by the ophthalmologist. As input data we use original and geometrically transformed retinal images from Messidor database divided into smaller blocks. In that way we enlarge the training dataset and increase classification accuracy.