Investigative Magnetic Resonance Imaging

Korean Society of Magnetic Resonance in Medicine (대한자기공명의과학회)
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Deep Learning in MR Motion Correction: a Brief Review and a New Motion Simulation Tool (view2Dmotion)

  • Lee, Seul (Department of Electrical and Electronic Engineering, Yonsei University) ;
  • Jung, Soozy (Department of Electrical and Electronic Engineering, Yonsei University) ;
  • Jung, Kyu-Jin (Department of Electrical and Electronic Engineering, Yonsei University) ;
  • Kim, Dong-Hyun (Department of Electrical and Electronic Engineering, Yonsei University)
  • Received : 2020.10.15
  • Accepted : 2020.11.11
  • Published : 2020.12.31
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Abstract

With the development of deep-learning techniques, the application of deep learning in MR imaging processing seems to be growing. Accordingly, deep learning has also been introduced in motion correction and seemed to work as well as do conventional motion-compensation methods. In this article, we review the motion-correction methods based on deep learning, focusing especially on the motion-simulation methods adopted. We then propose a new motion-simulation tool, which we call view2Dmotion.

Keywords

References

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