Japanese Journal of Radiology

, Volume 37, Issue 1, pp 73–80 | Cite as

Improvement of image quality at CT and MRI using deep learning

  • Toru Higaki
  • Yuko Nakamura
  • Fuminari Tatsugami
  • Takeshi Nakaura
  • Kazuo Awai
Invited Review


Deep learning has been developed by computer scientists. Here, we discuss techniques for improving the image quality of diagnostic computed tomography and magnetic resonance imaging with the aid of deep learning. We categorize the techniques for improving the image quality as “noise and artifact reduction”, “super resolution” and “image acquisition and reconstruction”. For each category, we present and outline the features of some studies.


Deep learning Image quality improvement Computed tomography Magnetic resonance imaging 



Kazuo Awai received following research grant: Research Grant, Canon Medical systems, paid to the institution. Research Grant, Hitachi, paid to the institution.

Compliance with ethical standards

Conflict of interest

The other authors declare that they have no conflict of interest.

Ethical statement



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Copyright information

© Japan Radiological Society 2018

Authors and Affiliations

  1. 1.Department of Diagnostic Radiology, Graduate School of Biomedical and Health ScienceHiroshima UniversityHiroshimaJapan
  2. 2.Department of Diagnostic Radiology, Graduate School of Medical SciencesKumamoto UniversityKumamotoJapan

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