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Impact of a Deep Learning-based Super-resolution Image Reconstruction Technique on High-contrast Computed Tomography: A Phantom Study.
Sato, Hideyuki; Fujimoto, Shinichiro; Tomizawa, Nobuo; Inage, Hidekazu; Yokota, Takuya; Kudo, Hikaru; Fan, Ruiheng; Kawamoto, Keiichi; Honda, Yuri; Kobayashi, Takayuki; Minamino, Tohru; Kogure, Yosuke.
Afiliación
  • Sato H; Department of Radiological Technology, Juntendo University Hospital, Tokyo, Japan.
  • Fujimoto S; Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan. Electronic address: blanks-fujimo@tj8.so-net.ne.jp.
  • Tomizawa N; Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan.
  • Inage H; Department of Radiological Technology, Juntendo University Hospital, Tokyo, Japan.
  • Yokota T; Department of Radiological Technology, Juntendo University Hospital, Tokyo, Japan.
  • Kudo H; Department of Radiological Technology, Juntendo University Hospital, Tokyo, Japan.
  • Fan R; Department of Radiological Technology, Juntendo University Hospital, Tokyo, Japan.
  • Kawamoto K; Department of Radiological Technology, Juntendo University Hospital, Tokyo, Japan.
  • Honda Y; Department of Radiological Technology, Juntendo University Hospital, Tokyo, Japan.
  • Kobayashi T; Department of Radiological Technology, Kitasato University Kitasato Institute Hospital, Tokyo, Japan.
  • Minamino T; Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan.
  • Kogure Y; Department of Radiological Technology, Juntendo University Hospital, Tokyo, Japan.
Acad Radiol ; 30(11): 2657-2665, 2023 Nov.
Article en En | MEDLINE | ID: mdl-36690564
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Texto completo: 1 Banco de datos: MEDLINE Idioma: En Revista: Acad Radiol Asunto de la revista: RADIOLOGIA Año: 2023 Tipo del documento: Article País de afiliación: Japón
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Banco de datos: MEDLINE Idioma: En Revista: Acad Radiol Asunto de la revista: RADIOLOGIA Año: 2023 Tipo del documento: Article País de afiliación: Japón