A method for the automatic detection of myopia in Optos fundus images based on deep learning | |
Shi, Zhengjin2; Wang, Tianyu2; Huang Z(黄钲)1,3,4; Xie, Feng2; Song GL(宋国立)3,4 | |
刊名 | International Journal for Numerical Methods in Biomedical Engineering
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2021 | |
卷号 | 37期号:6页码:1-15 |
关键词 | convolutional neural network deep learning image processing myopia optometry Optos fundus image |
ISSN号 | 2040-7939 |
产权排序 | 2 |
英文摘要 | Myopia detection is significant for preventing irreversible visual impairment and diagnosing myopic retinopathy. To improve the detection efficiency and accuracy, a Myopia Detection Network (MDNet) that combines the advantages of dense connection and Residual Squeeze-and-Excitation attention is proposed in this paper to automatically detect myopia in Optos fundus images. First, an automatic optic disc recognition method is applied to extract the Regions of Interest and remove the noise disturbances; then, data augmentation techniques are implemented to enlarge the data set and prevent overfitting; moreover, an MDNet composed of Attention Dense blocks is constructed to detect myopia in Optos fundus images. The results show that the Mean Absolute Error of the Spherical Equivalent detected by this network can reach 1.1150 D (diopter), which verifies the feasibility and applicability of this method for the automatic detection of myopia in Optos fundus images. |
资助项目 | National Key R&D Program of China[2017YFB1303003] ; National Natural Science Foundation of China[62073314] ; National Natural Science Foundation of China[61821005] ; Youth Innovation Promotion Association of the Chinese Academy of Sciences[2019205] ; Youth Innovation Promotion Association of the Chinese Academy of Sciences[GQRC-19-20] ; Special Fund for High-level Talents (Shizhen Zhong Team) of the People's Government of Luzhou Southwestern Medical University ; China Postdoctoral Science Foundation[2020M670815] |
WOS关键词 | EXUDATE DETECTION |
WOS研究方向 | Engineering ; Mathematical & Computational Biology ; Mathematics |
语种 | 英语 |
WOS记录号 | WOS:000640885300001 |
资助机构 | Youth Innovation Promotion Association of the Chinese Academy of Sciences, Grant/Award Number: 2019205 ; China Postdoctoral Science Foundation, Grant/Award Number: 2020M670815 ; National Key R&D Program of China, Grant/Award Number: 2017YFB1303003 ; National Natural Science Foundation of China, Grant/Award Numbers: 61821005, 62073314 |
内容类型 | 期刊论文 |
源URL | [http://ir.sia.cn/handle/173321/28763] ![]() |
专题 | 沈阳自动化研究所_机器人学研究室 |
通讯作者 | Song GL(宋国立) |
作者单位 | 1.University of Chinese Academy of Sciences, Beijing, China 2.School of Automation and Electrical Engineering, Shenyang Ligong University, Shenyang, China 3.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China 4.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang, China |
推荐引用方式 GB/T 7714 | Shi, Zhengjin,Wang, Tianyu,Huang Z,et al. A method for the automatic detection of myopia in Optos fundus images based on deep learning[J]. International Journal for Numerical Methods in Biomedical Engineering,2021,37(6):1-15. |
APA | Shi, Zhengjin,Wang, Tianyu,Huang Z,Xie, Feng,&Song GL.(2021).A method for the automatic detection of myopia in Optos fundus images based on deep learning.International Journal for Numerical Methods in Biomedical Engineering,37(6),1-15. |
MLA | Shi, Zhengjin,et al."A method for the automatic detection of myopia in Optos fundus images based on deep learning".International Journal for Numerical Methods in Biomedical Engineering 37.6(2021):1-15. |
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