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Improving lesion conspicuity in abdominal dual-energy CT with deep learning image reconstruction: a prospective study with five readers.
Zhong, Jingyu; Wang, Lingyun; Shen, Hailin; Li, Jianying; Lu, Wei; Shi, Xiaomeng; Xing, Yue; Hu, Yangfan; Ge, Xiang; Ding, Defang; Yan, Fuhua; Du, Lianjun; Yao, Weiwu; Zhang, Huan.
Afiliação
  • Zhong J; Department of Imaging, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200336, China.
  • Wang L; Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
  • Shen H; Department of Radiology, Suzhou Kowloon Hospital, Shanghai Jiao Tong University School of Medicine, Suzhou, 215028, China.
  • Li J; Computed Tomography Research Center, GE Healthcare, Beijing, 100176, China.
  • Lu W; Computed Tomography Research Center, GE Healthcare, Shanghai, 201203, China.
  • Shi X; Department of Materials, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK.
  • Xing Y; Department of Imaging, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200336, China.
  • Hu Y; Department of Imaging, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200336, China.
  • Ge X; Department of Imaging, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200336, China.
  • Ding D; Department of Imaging, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200336, China.
  • Yan F; Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
  • Du L; Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China. 13601745690@163.com.
  • Yao W; Department of Imaging, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200336, China. yaoweiwuhuan@163.com.
  • Zhang H; Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China. huanzhangy@163.com.
Eur Radiol ; 33(8): 5331-5343, 2023 Aug.
Article em En | MEDLINE | ID: mdl-36976337
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Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Aprendizado Profundo Tipo de estudo: Observational_studies / Prognostic_studies Limite: Humans Idioma: En Revista: Eur Radiol Assunto da revista: RADIOLOGIA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China
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: Observational_studies / Prognostic_studies Limite: Humans Idioma: En Revista: Eur Radiol Assunto da revista: RADIOLOGIA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China