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

초록

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.

키워드

Deep learningMachine learningMotion artifactMotion correctionMotion simulation
제목
Deep Learning in MR Motion Correction: a Brief Review and a New Motion Simulation Tool (view2Dmotion)
제목 (타언어)
Deep Learning in MR Motion Correction: a Brief Review and a New Motion Simulation Tool (view2Dmotion)
저자
이슬정수지Jung, Kyu-Jin김동현
DOI
10.13104/imri.2020.24.4.196
발행일
2020-12
저널명
Investigative Magnetic Resonance Imaging
24
4
페이지
196 ~ 206