首页> 外文会议>IEEE Region 10 Symposium >Automatic Detection of Eye Cataract using Deep Convolution Neural Networks (DCNNs)
【24h】

Automatic Detection of Eye Cataract using Deep Convolution Neural Networks (DCNNs)

机译:使用深度卷积神经网络(DCNN)自动检测白内障

获取原文

摘要

Eye cataract is a condition in which the lens of the eye becomes clouding or less transparent. This affects the clear vision and is the most prevailing causes of blindness. Therefore, early cataract detection and prevention may reduce the blindness rate and surgery pain of the patients. This paper presents an eye cataract detection system using Deep Convolution Neural Network (DCNNs) comprising two modules: training and testing. The proposed DCNNs architecture is trained, validated and tested with retinal fundus images. Experimental result shows that the proposed system is capable of detecting eye cataract with high accuracy.
机译:眼白内障是指晶状体混浊或不透明的情况。这会影响清晰的视力,并且是导致失明的最主要原因。因此,及早发现和预防白内障可以减少患者的失明率和手术痛苦。本文提出了一种使用深度卷积神经网络(DCNN)的眼白内障检测系统,该系统包括两个模块:训练和测试。所提出的DCNNs体系结构已通过视网膜眼底图像进行了培训,验证和测试。实验结果表明,该系统能够高精度地检测出白内障。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号