Institute of Computing Technology, Chinese Academy IR
Application of a deep convolutional neural network in the diagnosis of neonatal ocular fundus hemorrhage | |
Wang, Binbin1; Xiao, Li2; Liu, Yang2; Wang, Jing3; Liu, Beihong1; Li, Tengyan1; Ma, Xu1; Zhao, Yi2 | |
2018-12-21 | |
发表期刊 | BIOSCIENCE REPORTS |
ISSN | 0144-8463 |
卷号 | 38页码:8 |
摘要 | There is a disparity between the increasing application of digital retinal imaging to neonatal ocular screening and slowly growing number of pediatric ophthalmologists. Assistant tools that can automatically detect ocular disorders may be needed. In present study, we develop a deep convolutional neural network (DCNN) for automated classification and grading of retinal hemorrhage. We used 48,996 digital fundus images from 3770 newborns with retinal hemorrhage of different severity (grade 1, 2 and 3) and normal controls from a large cross-sectional investigation in China. The DCNN was trained for automated grading of retinal hemorrhage (multiclass classification problem: hemorrhage-free and grades 1, 2 and 3) and then validated for its performance level. The DCNN yielded an accuracy of 97.85 to 99.96%, and the area under the receiver operating characteristic curve was 0.989-1.000 in the binary classification of neonatal retinal hemorrhage (i.e., one classification vs. the others). The overall accuracy with regard to the multiclass classification problem was 97.44%. This is the first study to show that a DCNN can detect and grade neonatal retinal hemorrhage at high performance levels. Artificial intelligence will play more positive roles in ocular healthcare of newborns and children. |
DOI | 10.1042/BSR20180497 |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Key Research and Development Program of China[2016YFC1000307] ; National Science and Technology Basic Work[2014FY130100] ; CAS Pioneer Hundred Talents Program[2017-074] |
WOS研究方向 | Biochemistry & Molecular Biology ; Cell Biology |
WOS类目 | Biochemistry & Molecular Biology ; Cell Biology |
WOS记录号 | WOS:000454266100019 |
出版者 | PORTLAND PRESS LTD |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.204/handle/2XEOYT63/3489 |
专题 | 中国科学院计算技术研究所期刊论文_英文 |
通讯作者 | Ma, Xu; Zhao, Yi |
作者单位 | 1.Natl Res Inst Family Planning, Ctr Genet, Beijing 100081, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, State Key Lab Comp Architecture, Key Lab Intelligent Informat Proc,Adv Comp Res Ct, Beijing 100190, Peoples R China 3.Capital Med Univ, Sch Basic Med Sci, Dept Med Genet & Dev Biol, Beijing, Peoples R China |
推荐引用方式 GB/T 7714 | Wang, Binbin,Xiao, Li,Liu, Yang,et al. Application of a deep convolutional neural network in the diagnosis of neonatal ocular fundus hemorrhage[J]. BIOSCIENCE REPORTS,2018,38:8. |
APA | Wang, Binbin.,Xiao, Li.,Liu, Yang.,Wang, Jing.,Liu, Beihong.,...&Zhao, Yi.(2018).Application of a deep convolutional neural network in the diagnosis of neonatal ocular fundus hemorrhage.BIOSCIENCE REPORTS,38,8. |
MLA | Wang, Binbin,et al."Application of a deep convolutional neural network in the diagnosis of neonatal ocular fundus hemorrhage".BIOSCIENCE REPORTS 38(2018):8. |
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