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Deep Learning for Retrospective Motion Correction in MRI: A Comprehensive Review. (arXiv:2305.06739v1 [eess.IV])
cs.CV updates on arXiv.org arxiv.org
Motion represents one of the major challenges in magnetic resonance imaging
(MRI). Since the MR signal is acquired in frequency space, any motion of the
imaged object leads to complex artefacts in the reconstructed image in addition
to other MR imaging artefacts. Deep learning has been frequently proposed for
motion correction at several stages of the reconstruction process. The wide
range of MR acquisition sequences, anatomies and pathologies of interest, and
motion patterns (rigid vs. deformable and random vs. regular) …
acquired arxiv challenges deep learning image imaging leads major mri retrospective review signal space