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Correction to: Image quality of ultralow-dose chest CT using deep learning techniques: potential superiority of vendor-agnostic post-processing over vendor-specific techniques

European Radiology (2021)Cite this article

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Correction to: European Radiology

https://doi.org/10.1007/s00330-020-07537-7

The original version of this article, published on 07 January 2021, unfortunately contained a mistake. The following correction has therefore been made in the original: The information that Ju Gang Nam and Chulkyun Ahn contributed equally to this work was missing. The original article has been corrected.

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Author notes

  1. Ju Gang Nam and Chulkyun Ahn contributed equally to this work.

Affiliations

  1. Department of Radiology, Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul National University Medical Research Center, 101 Daehak-ro, Jongno-gu, Seoul, 03080, South Korea

    Ju Gang Nam, Hyewon Choi, Wonju Hong, Jongsoo Park, Jong Hyo Kim & Jin Mo Goo

  2. Department of Transdisciplinary Studies, Program in Biomedical Radiation Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, 08826, South Korea

    Chulkyun Ahn & Jong Hyo Kim

  3. Center for Medical-IT Convergence Technology Research, Advanced Institutes of Convergence Technology, Suwon, 16229, South Korea

    Jong Hyo Kim

  4. Cancer Research Institute, Seoul National University, Seoul, 03080, South Korea

    Jin Mo Goo

Authors
  1. Ju Gang Nam
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  2. Chulkyun Ahn
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  3. Hyewon Choi
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  4. Wonju Hong
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  5. Jongsoo Park
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  6. Jong Hyo Kim
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  7. Jin Mo Goo
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Corresponding author

Correspondence to Jin Mo Goo.

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The online version of the original article can be found at https://doi.org/10.1007/s00330-020-07537-7

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Nam, J.G., Ahn, C., Choi, H. et al. Correction to: Image quality of ultralow-dose chest CT using deep learning techniques: potential superiority of vendor-agnostic post-processing over vendor-specific techniques. Eur Radiol (2021). https://doi.org/10.1007/s00330-021-07733-z

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