Retinal Disease Classification using Deep Learning

Retinal Disease Classification using Deep Learning

S.A. Shivarkar, Aishwaryaraj Chandel, Sumit Maradkar, Umakant Dodtalle

Department of CSE

JSPM’s JSCOE,Pune, India

Abstract- Retinal disease, which consist a varying range of eye disorders, can be a serious and alarming threat to vision and ocular health. Timely diagnosis is the most important as in early stages it is easier to plan the treatment and intervention. In recent years, the involvement of the deep learning methodologies into the field of ophthalmology has been realized through medical imaging that has revolutionized the ophthalmology study. This research investigates the use of deep learning methods that help in classification of retinal diseases through high-resolution cadaver images. The focus of this work is providing an entirely operational and cutting-edge system for retinal disease classification using deep learning covering the main technical challenges and issues on ethics. The made model is a major advancement in the process of detecting retinal diseases with the aim of improving the quality and efficiency of the eye care. The model is also expected to improve patient outcomes.

Keywords: Re-winding, health classification, deep learning, RNN.