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Computer-Aided Diagnosis of Ophthalmic Diseases Using OCT Based on Deep Learning: A Review

机译:基于深度学习的10月使用OCT的计算机辅助诊断眼科疾病:综述

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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 noninvasive 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.
机译:深度学习可以有效地提取图像的隐藏特征,近年来在医学图像识别中迅速发展。眼科疾病是影响健康生活的关键因素之一。同时,光学相干断层扫描(OCT)具有非侵入性和高分辨率的特点,并已成为眼科疾病临床诊断中的主流影像技术。因此,基于深度学习使用10月的眼科疾病的计算机辅助诊断引起了广泛的研究热潮。在本文中,我们审查了OCT,OCT公共数据集的成像方法和应用。我们详细介绍了近年来OCT的多种眼科疾病的计算机辅助诊断系统,包括与年龄相关的黄斑变性,青光眼,糖尿病MATEMA等,以及10月深入学习面临的主要挑战概述成像。

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