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European Radiology

, Volume 29, Issue 8, pp 4526–4527 | Cite as

Correction to: Deep learning reconstruction improves image quality of abdominal ultra-high-resolution CT

  • Motonori Akagi
  • Yuko NakamuraEmail author
  • Toru Higaki
  • Keigo Narita
  • Yukiko Honda
  • Jian Zhou
  • Zhou Yu
  • Naruomi Akino
  • Kazuo Awai
Correction
  • 337 Downloads

Correction to: European Radiology

  https://doi.org/10.1007/s00330-019-06170-3

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.
Fig. 3

Hepatic arterial (ac) and equilibrium phase images (df) of a 76-year-old man. Reconstruction was with hybrid-IR (a, d), MBIR (b, e), and DLR (c, f). The image noise was lower on the DLR image than on the other images

Notes

Copyright information

© European Society of Radiology 2019

Authors and Affiliations

  • Motonori Akagi
    • 1
  • Yuko Nakamura
    • 1
    Email author
  • Toru Higaki
    • 1
  • Keigo Narita
    • 1
  • Yukiko Honda
    • 1
  • Jian Zhou
    • 2
  • Zhou Yu
    • 2
  • Naruomi Akino
    • 3
  • Kazuo Awai
    • 1
  1. 1.Diagnostic RadiologyHiroshima UniversityHiroshimaJapan
  2. 2.Canon Medical Research USA, Inc.Vernon HillsUSA
  3. 3.Canon Medical Systems Co. Ltd.OtawaraJapan

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