Investig Magn Reson Imaging.  2020 Dec;24(4):196-206. 10.13104/imri.2020.24.4.196.

Deep Learning in MR Motion Correction:a Brief Review and a New Motion Simulation Tool (view2Dmotion)

Affiliations
  • 1Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Korea

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.

Keyword

Deep learning; Machine learning; Motion artifact; Motion correction; Motion simulation
Full Text Links
  • IMRI
Actions
Cited
CITED
export Copy
Close
Share
  • Twitter
  • Facebook
Similar articles
Copyright © 2021 by Korean Association of Medical Journal Editors. All rights reserved.     E-mail: koreamed@kamje.or.kr