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首页> 外文会议>IEEE International Conference on Intelligent Computer Communication and Processing >Automated Age-Related Macular Degeneration and Diabetic Macular Edema Detection on OCT Images using Deep Learning
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Automated Age-Related Macular Degeneration and Diabetic Macular Edema Detection on OCT Images using Deep Learning

机译：使用深度学习的自动相关年龄相关性黄斑和糖尿病黄斑水肿检测OCT图像

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摘要

Age-related macular degeneration (AMD) is an eye disease that damages the retina, causing vision loss. Diabetic macular edema (DME) is also a form of vision loss for diabetic people. It is therefore crucial to detect AMD and DME in the early stages for the timely treatment of the eye and the prevention of any vision impairment. Automatic detection of DME and AMD on optical coherence tomography (OCT) images are presented in this paper. The method used is based on training a deep learning algorithm to classify them into healthy, dry AMD, wet AMD and DME categories. This method outperforms a transfer learning based method proposed recently in the literature for classification of OCT images into AMD and DME categories.
机译：年龄相关的黄斑变性（AMD）是一种损害视网膜的眼部疾病，导致视力丧失。糖尿病黄斑水肿（DME）也是糖尿病患者视力丧失的一种形式。因此，在早期阶段检测AMD和DME是至关重要的，以便及时治疗眼睛和预防任何视力障碍。本文提出了在光学相干断层扫描（OCT）图像上的DME和AMD的自动检测。使用的方法是基于培训深度学习算法，将它们分类为健康，干燥的AMD，湿AMD和DME类别。该方法优于最近在文献中提出的基于转移学习的方法，使OCT图像分类为AMD和DME类别。

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