Advances in Diabetic Retinopathy: A review of Detection and Progression Assessment Techniques

Abstract

One of the most prevalent consequences of diabetes is diabetic retinopathy. Unfortunately, many patients are unaware of their signs and symptoms until it is already too late for appropriate therapy. The investigation of induced potential responses of the retina, optical nerve, and optical brain centre will clear the way for early diagnosis and prognosis throughout therapy. We present in this article an artificial-neural-network-based method for classifying diabetic retinopathy subjects based on changes in visual evoked potential spectral components, as well as an anatomically realistic computer systems model of the human eye in normal and retinopathy conditions in a virtual environment using 3D Max Studio and Windows Movie Maker.