Stop moving: MR motion correction as an opportunity for artificial intelligence

Subject motion is a long-standing problem of magnetic resonance imaging (MRI), which can seriously deteriorate the image quality. Various prospective and retrospective methods have been proposed for MRI motion correction, among which deep learning approaches have achieved state-of-the-art motion cor...

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Bibliographic Details
Published in:	Magma (New York, N.Y.) Vol. 37; no. 3; pp. 397 - 409
Main Authors:	Zhou, Zijian, Hu, Peng, Qi, Haikun
Format:	Journal Article
Language:	English
Published:	Cham Springer International Publishing 01.07.2024
Subjects:	Algorithms Artificial Intelligence Basic Science - Reconstruction algorithms and artificial intelligence Biomedical Engineering and Bioengineering Brain - diagnostic imaging Computer Appl. in Life Sciences Deep Learning Health Informatics Humans Image Processing, Computer-Assisted - methods Imaging Magnetic Resonance Imaging - methods Medicine Medicine & Public Health Motion Movement Neural Networks, Computer Radiology Review Solid State Physics Motion correction Motion estimation MRI reconstruction Artificial intelligence
ISSN:	1352-8661, 1352-8661
Online Access:	Get full text
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