Deep Learning in MR Motion Correction: a Brief Review and a New Motion Simulation Tool (view2Dmotion)
Seul Lee, Soozy Jung, Kyu‐Jin Jung, Dong‐Hyun Kim
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.
Topics & Concepts
Motion (physics)MedicineArtificial intelligenceComputer scienceMedical physicsAdvanced MRI Techniques and ApplicationsAtomic and Subatomic Physics ResearchNMR spectroscopy and applications