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PCG-net: feature adaptive deep learning for automated head and neck organs-at-risk segmentation.
Luan, Shunyao; Wei, Changchao; Ding, Yi; Xue, Xudong; Wei, Wei; Yu, Xiao; Wang, Xiao; Ma, Chi; Zhu, Benpeng.
Afiliación
  • Luan S; School of Integrated Circuit, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China.
  • Wei C; Key Laboratory of Artificial Micro and Nano-structures of Ministry of Education, Center for Theoretical Physics, School of Physics and Technology, Wuhan University, Wuhan, China.
  • Ding Y; Department of Radiation Oncology, Hubei Cancer Hospital, TongJi Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
  • Xue X; Department of Radiation Oncology, Hubei Cancer Hospital, TongJi Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
  • Wei W; Department of Radiation Oncology, Hubei Cancer Hospital, TongJi Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
  • Yu X; Department of Radiation Oncology, The First Affiliated Hospital of University of Science and Technology of China, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China.
  • Wang X; Department of Radiation Oncology, Rutgers-Cancer Institute of New Jersey, Rutgers-Robert Wood Johnson Medical School, New Brunswick, NJ, United States.
  • Ma C; Department of Radiation Oncology, Rutgers-Cancer Institute of New Jersey, Rutgers-Robert Wood Johnson Medical School, New Brunswick, NJ, United States.
  • Zhu B; School of Integrated Circuit, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China.
Front Oncol ; 13: 1177788, 2023.
Article en En | MEDLINE | ID: mdl-37927463
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Front Oncol Año: 2023 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza
Texto completo
Añadir a Mi BVS
Imprimir
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PubMed Links
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Front Oncol Año: 2023 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza