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X-ray Cherenkov-luminescence tomography reconstruction with a three-component deep learning algorithm: Swin transformer, convolutional neural network, and locality module.
Feng, Jinchao; Zhang, Hu; Geng, Mengfan; Chen, Hanliang; Jia, Kebin; Sun, Zhonghua; Li, Zhe; Cao, Xu; Pogue, Brian W.
Afiliación
  • Feng J; Beijing University of Technology, Beijing Key Laboratory of Computational Intelligence and Intelligent System, Faculty of Information Technology, Beijing, China.
  • Zhang H; Beijing Laboratory of Advanced Information Networks, Beijing, China.
  • Geng M; Beijing University of Technology, Beijing Key Laboratory of Computational Intelligence and Intelligent System, Faculty of Information Technology, Beijing, China.
  • Chen H; Beijing University of Technology, Beijing Key Laboratory of Computational Intelligence and Intelligent System, Faculty of Information Technology, Beijing, China.
  • Jia K; Beijing University of Technology, Beijing Key Laboratory of Computational Intelligence and Intelligent System, Faculty of Information Technology, Beijing, China.
  • Sun Z; Beijing University of Technology, Beijing Key Laboratory of Computational Intelligence and Intelligent System, Faculty of Information Technology, Beijing, China.
  • Li Z; Beijing Laboratory of Advanced Information Networks, Beijing, China.
  • Cao X; Beijing University of Technology, Beijing Key Laboratory of Computational Intelligence and Intelligent System, Faculty of Information Technology, Beijing, China.
  • Pogue BW; Beijing Laboratory of Advanced Information Networks, Beijing, China.
J Biomed Opt ; 28(2): 026004, 2023 02.
Article en En | MEDLINE | ID: mdl-36818584
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Tomografía Computarizada por Rayos X / Aprendizaje Profundo Tipo de estudio: Prognostic_studies Idioma: En Revista: J Biomed Opt Asunto de la revista: ENGENHARIA BIOMEDICA / OFTALMOLOGIA Año: 2023 Tipo del documento: Article País de afiliación: China
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Tomografía Computarizada por Rayos X / Aprendizaje Profundo Tipo de estudio: Prognostic_studies Idioma: En Revista: J Biomed Opt Asunto de la revista: ENGENHARIA BIOMEDICA / OFTALMOLOGIA Año: 2023 Tipo del documento: Article País de afiliación: China