An Annotation-Free Restoration Network for Cataractous Fundus Images

Li，Heng1; Liu，Haofeng2; Hu，Yan2; Fu，Huazhu3; Zhao，Yitian4; Miao，Hanpei2; Liu，Jiang5

2022-07

10.1109/TMI.2022.3147854

IEEE Transactions on Medical Imaging   影响因子和分区

1558-254X

Cataracts fundus image restoration high-frequency component domain adaptation

SCI ; EI

第一 ; 共同第一 ; 通讯

20220611613306

Diagnosis ; Image annotation ; Image enhancement ; Image segmentation ; Patient treatment ; Restoration

Medicine and Pharmacology:461.6 ; Data Processing and Image Processing:723.2

CLINICAL MEDICINE

IEEE

1.Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China. (e-mail: lih3@sustech.edu.cn)
2.Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China.
3.Institute of High Performance Computing, Agency for Science, Technology and Research, Singapore.
4.Cixi Institute of Biomedical Engineering, Ningbo Institute of Industrial Technology, Chinese Academy of Sciences, Ningbo 315201, China.
5.Research Institute of Trustworthy Autonomous Systems, Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China.

Li，Heng,Liu，Haofeng,Hu，Yan,et al. An Annotation-Free Restoration Network for Cataractous Fundus Images[J]. IEEE Transactions on Medical Imaging,2022,41(7):1699-1710.

Li，Heng.,Liu，Haofeng.,Hu，Yan.,Fu，Huazhu.,Zhao，Yitian.,...&Liu，Jiang.(2022).An Annotation-Free Restoration Network for Cataractous Fundus Images.IEEE Transactions on Medical Imaging,41(7),1699-1710.

Li，Heng,et al."An Annotation-Free Restoration Network for Cataractous Fundus Images".IEEE Transactions on Medical Imaging 41.7(2022):1699-1710.