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Image quality improvement with deep learning-based reconstruction on abdominal ultrahigh-resolution CT: A phantom study.
Shirasaka, Takashi; Kojima, Tsukasa; Funama, Yoshinori; Sakai, Yuki; Kondo, Masatoshi; Mikayama, Ryoji; Hamasaki, Hiroshi; Kato, Toyoyuki; Ushijima, Yasuhiro; Asayama, Yoshiki; Nishie, Akihiro.
Afiliação
  • Shirasaka T; Division of Radiology, Department of Medical Technology, Kyushu University Hospital, Fukuoka, Japan.
  • Kojima T; Division of Radiology, Department of Medical Technology, Kyushu University Hospital, Fukuoka, Japan.
  • Funama Y; Department of Medical Physics, Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan.
  • Sakai Y; Division of Radiology, Department of Medical Technology, Kyushu University Hospital, Fukuoka, Japan.
  • Kondo M; Division of Radiology, Department of Medical Technology, Kyushu University Hospital, Fukuoka, Japan.
  • Mikayama R; Division of Radiology, Department of Medical Technology, Kyushu University Hospital, Fukuoka, Japan.
  • Hamasaki H; Division of Radiology, Department of Medical Technology, Kyushu University Hospital, Fukuoka, Japan.
  • Kato T; Division of Radiology, Department of Medical Technology, Kyushu University Hospital, Fukuoka, Japan.
  • Ushijima Y; Department of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
  • Asayama Y; Department of Advanced Imaging and Interventional Radiology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
  • Nishie A; Department of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
J Appl Clin Med Phys ; 22(7): 286-296, 2021 Jul.
Article em En | MEDLINE | ID: mdl-34159736
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Aprendizado Profundo Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Aprendizado Profundo Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article