Intensity-based 3D motion correction for cardiac MR images

Nil Stolt-Ansó, Vasiliki Sideri-Lampretsa, Maik Dannecker, Daniel Rueckert
3/31/2024
eess.IVcs.CV

No official code found. Best implementation: NILOIDE/CMR_intensity_3Dmoco (3 stars, last commit 2024-05-25).

Abstract

Cardiac magnetic resonance (CMR) image acquisition requires subjects to hold their breath while 2D cine images are acquired. This process assumes that the heart remains in the same position across all slices. However, differences in breathhold positions or patient motion introduce 3D slice misalignments. In this work, we propose an algorithm that simultaneously aligns all SA and LA slices by maximizing the pair-wise intensity agreement between their intersections. Unlike previous works, our approach is formulated as a subject-specific optimization problem and requires no prior knowledge of the underlying anatomy. We quantitatively demonstrate that the proposed method is robust against a large range of rotations and translations by synthetically misaligning 10 motion-free datasets and aligning them back using the proposed method.

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Code Implementations(1)

NILOIDE/CMR_intensity_3DmocoCommunity100%

We propose a method to mitigate the effect of inter-slice motion in CMR images for all SA and LA slices simultaneously by optimizing the 3D rotation and translation parameters on sampled intensities along slice intersections.

30PythonNov 26, 20232 years ago

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Cite this paper

@article{stoltans2024intensitybased,
  title  = {Intensity-based 3D motion correction for cardiac MR images},
  author = {Nil Stolt-Ansó and Vasiliki Sideri-Lampretsa and Maik Dannecker and Daniel Rueckert},
  year   = {2024},
  eprint = {2404.00767},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2404.00767v1}
}

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