DEEP LEARNING BASED RETINAL DISEASE DIAGNOSIS
Abstract - The proposed system uses optical coherence images to foster a framework to recognize retinal problems. To determine the retinal diseases in an effective manner, an accurate and computerized analysis of optical coherence images are used. In this proposed work, convolutional neural network is applied to detect multiple retinal diseases which is categorized by the dataset extracted from retinal features that is described along with fundus images. The database to categorize the retina diseases is obtained from retina’s structured analysis. The proposed work describes the ingenious elucidation that yields valuable detection of retinal problems. Deep learning uses convolutional network to achieve incredible success in the categorization of different retinal diseases. Convolutional neural network uses a visualization methods and it is trained with a retinal disease database which is available in the public platform. In this proposed work, research is done with variety of retinal feature as an aid to machine learning network for effective categorization of retinal images.
Keywords - Retina, Deep Learning, Prediction.