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Synergistically segmenting choroidal layer and vessel using deep learning for choroid structure analysis.
Zhu, Lei; Li, JunMeng; Zhu, Ruilin; Meng, Xiangxi; Rong, Pei; Zhang, Yibao; Jiang, Zhe; Geng, Mufeng; Qiu, Bin; Rong, Xin; Zhang, Yadi; Gu, Xiaopeng; Wang, Yuwei; Zhang, Zhiyue; Wang, Jing; Yang, Liu; Ren, Qiushi; Lu, Yanye.
Afiliação
  • Zhu L; Institute of Medical Technology, Peking University Health Science Center, Peking University, Beijing 100191, People's Republic of China.
  • Li J; Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing 100871, People's Republic of China.
  • Zhu R; Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen 5181071, People's Republic of China.
  • Meng X; Institute of Biomedical Engineering, Peking University Shenzhen Graduate School, Shenzhen 518055, People's Republic of China.
  • Rong P; Department of Ophthalmology, Peking University First Hospital, Beijing 100034, People's Republic of China.
  • Zhang Y; Department of Ophthalmology, Peking University First Hospital, Beijing 100034, People's Republic of China.
  • Jiang Z; Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital & Institute, Beijing 100142, People's Republic of China.
  • Geng M; Department of Ophthalmology, Peking University First Hospital, Beijing 100034, People's Republic of China.
  • Qiu B; Institute of Medical Technology, Peking University Health Science Center, Peking University, Beijing 100191, People's Republic of China.
  • Rong X; Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital & Institute, Beijing 100142, People's Republic of China.
  • Zhang Y; Institute of Medical Technology, Peking University Health Science Center, Peking University, Beijing 100191, People's Republic of China.
  • Gu X; Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing 100871, People's Republic of China.
  • Wang Y; Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen 5181071, People's Republic of China.
  • Zhang Z; Institute of Biomedical Engineering, Peking University Shenzhen Graduate School, Shenzhen 518055, People's Republic of China.
  • Wang J; Institute of Medical Technology, Peking University Health Science Center, Peking University, Beijing 100191, People's Republic of China.
  • Yang L; Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing 100871, People's Republic of China.
  • Ren Q; Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen 5181071, People's Republic of China.
  • Lu Y; Institute of Biomedical Engineering, Peking University Shenzhen Graduate School, Shenzhen 518055, People's Republic of China.
Phys Med Biol ; 67(8)2022 04 01.
Article em En | MEDLINE | ID: mdl-35299162
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Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Aprendizado Profundo Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Phys Med Biol Ano de publicação: 2022 Tipo de documento: Article
Texto completo
Adicionar na Minha BVS
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Aprendizado Profundo Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Phys Med Biol Ano de publicação: 2022 Tipo de documento: Article