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Multi-granularity learning of explicit geometric constraint and contrast for label-efficient medical image segmentation and differentiable clinical function assessment.
Meng, Yanda; Zhang, Yuchen; Xie, Jianyang; Duan, Jinming; Joddrell, Martha; Madhusudhan, Savita; Peto, Tunde; Zhao, Yitian; Zheng, Yalin.
Afiliação
  • Meng Y; Department of Eye and Vision Sciences, University of Liverpool, Liverpool, United Kingdom.
  • Zhang Y; Center for Bioinformatics, Peking University, Beijing, China.
  • Xie J; Department of Eye and Vision Sciences, University of Liverpool, Liverpool, United Kingdom.
  • Duan J; School of Computer Science, University of Birmingham, Birmingham, United Kingdom.
  • Joddrell M; Liverpool Centre for Cardiovascular Science, University of Liverpool and Liverpool Heart & Chest Hospital, Liverpool, United Kingdom; Department of Cardiovascular and Metabolic Medicine, University of Liverpool, Liverpool, United Kingdom.
  • Madhusudhan S; St Paul's Eye Unit, Liverpool University Hospitals NHS Foundation Trust, Liverpool, United Kingdom.
  • Peto T; School of Medicine, Dentistry and Biomedical Sciences, Queen's University Belfast, Belfast, United Kingdom.
  • Zhao Y; Institute of Biomedical Engineering, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Science, Ningbo, China; Ningbo Eye Hospital, Ningbo, China. Electronic address: yitian.zhao@nimte.ac.cn.
  • Zheng Y; Department of Eye and Vision Sciences, University of Liverpool, Liverpool, United Kingdom; Liverpool Centre for Cardiovascular Science, University of Liverpool and Liverpool Heart & Chest Hospital, Liverpool, United Kingdom. Electronic address: yalin.zheng@liverpool.ac.uk.
Med Image Anal ; 95: 103183, 2024 Jul.
Article em En | MEDLINE | ID: mdl-38692098
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article
Texto completo
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XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article