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Correction to: Deep learning reconstruction improves image quality of abdominal ultra-high-resolution CT.
Akagi, Motonori; Nakamura, Yuko; Higaki, Toru; Narita, Keigo; Honda, Yukiko; Zhou, Jian; Yu, Zhou; Akino, Naruomi; Awai, Kazuo.
Affiliation
  • Akagi M; Diagnostic Radiology, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, Japan.
  • Nakamura Y; Diagnostic Radiology, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, Japan. yukon@hiroshima-u.ac.jp.
  • Higaki T; Diagnostic Radiology, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, Japan.
  • Narita K; Diagnostic Radiology, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, Japan.
  • Honda Y; Diagnostic Radiology, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, Japan.
  • Zhou J; Canon Medical Research USA, Inc., Vernon Hills, IL, USA.
  • Yu Z; Canon Medical Research USA, Inc., Vernon Hills, IL, USA.
  • Akino N; Canon Medical Systems Co. Ltd., Otawara, Japan.
  • Awai K; Diagnostic Radiology, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, Japan.
Eur Radiol ; 29(8): 4526-4527, 2019 Aug.
Article in En | MEDLINE | ID: mdl-31134364
ABSTRACT
The original version of this article, published on 11 April 2019, unfortunately, contained a mistake. The following correction has therefore been made in the original The image in Fig. 3c was wrong. The corrected figure is given below. The original article has been corrected.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Eur Radiol Journal subject: RADIOLOGIA Year: 2019 Document type: Article Affiliation country:
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Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Eur Radiol Journal subject: RADIOLOGIA Year: 2019 Document type: Article Affiliation country: