Computer-aided diagnosis of ophthalmic diseases using OCT based on deep learning: A review

Abstract

Deep learning can effectively extract the hidden features of images and has developed rapidly in medical image recognition in recent years. Ophthalmic diseases are one of the critical factors affecting the healthy living. At the same time, optical coherence tomography (OCT) has the characteristics of non-invasive and high-resolution and has become the mainstream imaging technology in the clinical diagnosis of Ophthalmic diseases. Therefore, computer-aided diagnosis of ophthalmic diseases using OCT based on deep learning has caused a wide range of research craze. In this paper, we review the imaging methods and applications of OCT, the OCT public dataset. And we introduce in detail the computer-aided diagnosis system of multiple ophthalmic diseases using OCT in recent years, including age-related macular degeneration, glaucoma, diabetic macular edema and so on, and an overview of the main challenges faced by deep learning in OCT imaging.