181 citations · 270 across the 5 of their papers we have counts for
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eess.IV2023★ 81 cited
Deep Learning for Retrospective Motion Correction in MRI: A Comprehensive Review
Veronika Spieker, Hannah Eichhorn, Kerstin Hammernik +4
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 comp…
eess.IV2023★ 6 cited
Physics-Aware Motion Simulation for T2*-Weighted Brain MRI
Hannah Eichhorn, Kerstin Hammernik, Veronika Spieker +4
In this work, we propose a realistic, physics-aware motion simulation procedure for T2*-weighted magnetic resonance imaging (MRI) to improve learning-based motion correction. As T2…