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A generic fundus image enhancement network boosted by frequency self-supervised representation learning.
Li, Heng; Liu, Haofeng; Fu, Huazhu; Xu, Yanwu; Shu, Hai; Niu, Ke; Hu, Yan; Liu, Jiang.
Afiliação
  • Li H; Research Institute of Trustworthy Autonomous Systems and Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China. Electronic address: lih3@sustech.edu.cn.
  • Liu H; Research Institute of Trustworthy Autonomous Systems and Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China. Electronic address: liuhf2020@mail.sustech.edu.cn.
  • Fu H; Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), Singapore.
  • Xu Y; School of Future Technology, South China University of Technology, Guangzhou, China; Pazhou Lab, Guangzhou, China.
  • Shu H; Department of Biostatistics, School of Global Public Health, New York University, NY, USA.
  • Niu K; Computer School, Beijing Information Science and Technology University, Beijing, China.
  • Hu Y; Research Institute of Trustworthy Autonomous Systems and Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China. Electronic address: huy3@sustech.edu.cn.
  • Liu J; Research Institute of Trustworthy Autonomous Systems and Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China; Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China; Guangdong Provincia
Med Image Anal ; 90: 102945, 2023 Dec.
Article em En | MEDLINE | ID: mdl-37703674
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: Med Image Anal Assunto da revista: DIAGNOSTICO POR IMAGEM Ano de publicação: 2023 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: Med Image Anal Assunto da revista: DIAGNOSTICO POR IMAGEM Ano de publicação: 2023 Tipo de documento: Article