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Adaptive scatter kernel deconvolution modeling for cone-beam CT scatter correction via deep reinforcement learning.
Piao, Zun; Deng, Wenxin; Huang, Shuang; Lin, Guoqin; Qin, Peishan; Li, Xu; Wu, Wangjiang; Qi, Mengke; Zhou, Linghong; Li, Bin; Ma, Jianhui; Xu, Yuan.
Afiliación
  • Piao Z; School of Biomedical Engineering, Southern Medical University, Guangzhou, China.
  • Deng W; School of Biomedical Engineering, Southern Medical University, Guangzhou, China.
  • Huang S; School of Biomedical Engineering, Southern Medical University, Guangzhou, China.
  • Lin G; School of Biomedical Engineering, Southern Medical University, Guangzhou, China.
  • Qin P; School of Biomedical Engineering, Southern Medical University, Guangzhou, China.
  • Li X; School of Biomedical Engineering, Southern Medical University, Guangzhou, China.
  • Wu W; School of Biomedical Engineering, Southern Medical University, Guangzhou, China.
  • Qi M; School of Biomedical Engineering, Southern Medical University, Guangzhou, China.
  • Zhou L; School of Biomedical Engineering, Southern Medical University, Guangzhou, China.
  • Li B; State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China.
  • Ma J; Department of Radiation Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, China.
  • Xu Y; School of Biomedical Engineering, Southern Medical University, Guangzhou, China.
Med Phys ; 51(2): 1163-1177, 2024 Feb.
Article en En | MEDLINE | ID: mdl-37459053

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Algoritmos / Procesamiento de Imagen Asistido por Computador Idioma: En Revista: Med Phys Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Algoritmos / Procesamiento de Imagen Asistido por Computador Idioma: En Revista: Med Phys Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Estados Unidos