Deep learning for retrospective motion correction in MRI: a comprehensive review

V Spieker, H Eichhorn, K Hammernik… - … on Medical Imaging, 2023 - ieeexplore.ieee.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 …

Deep learning for accelerated and robust MRI reconstruction

R Heckel, M Jacob, A Chaudhari, O Perlman… - … Resonance Materials in …, 2024 - Springer
Deep learning (DL) has recently emerged as a pivotal technology for enhancing magnetic
resonance imaging (MRI), a critical tool in diagnostic radiology. This review paper provides …

Deep learning for accelerated and robust MRI reconstruction: a review

R Heckel, M Jacob, A Chaudhari, O Perlman… - arxiv preprint arxiv …, 2024 - arxiv.org
Deep learning (DL) has recently emerged as a pivotal technology for enhancing magnetic
resonance imaging (MRI), a critical tool in diagnostic radiology. This review paper provides …

Physics-informed deep learning for motion-corrected reconstruction of quantitative brain MRI

H Eichhorn, V Spieker, K Hammernik, E Saks… - … Conference on Medical …, 2024 - Springer
We propose PHIMO, a physics-informed learning-based motion correction method tailored
to quantitative MRI. PHIMO leverages information from the signal evolution to exclude …

SISMIK for brain MRI: Deep-learning-based motion estimation and model-based motion correction in k-space

O Dabrowski, JL Falcone, A Klauser… - … on Medical Imaging, 2024 - ieeexplore.ieee.org
MRI, a widespread non-invasive medical imaging modality, is highly sensitive to patient
motion. Despite many attempts over the years, motion correction remains a difficult problem …

MRI Motion Correction Through Disentangled CycleGAN Based on Multi-Mask K-Space Subsampling

G Chen, H **e, X Rao, X Liu, M Otikovs… - … on Medical Imaging, 2024 - ieeexplore.ieee.org
This work proposes a new retrospective motion correction method, termed DCGAN-MS,
which employs disentangled CycleGAN based onmulti-mask k-space subsampling (DCGAN …

IM-MoCo: Self-supervised MRI Motion Correction Using Motion-Guided Implicit Neural Representations

Z Al-Haj Hemidi, C Weihsbach, MP Heinrich - International Conference on …, 2024 - Springer
Abstract Motion artifacts in Magnetic Resonance Imaging (MRI) arise due to relatively long
acquisition times and can compromise the clinical utility of acquired images. Traditional …

IM-MoCo: Self-supervised MRI Motion Correction using Motion-Guided Implicit Neural Representations

ZAH Hemidi, C Weihsbach, MP Heinrich - arxiv preprint arxiv:2407.02974, 2024 - arxiv.org
Motion artifacts in Magnetic Resonance Imaging (MRI) arise due to relatively long
acquisition times and can compromise the clinical utility of acquired images. Traditional …