Intensity-based 3D motion correction for cardiac MR images (2404.00767v1)
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.
- “Correction of misaligned slices in multi-slice cardiovascular magnetic resonance using slice-to-volume registration,” Journal of Cardiovascular Magnetic Resonance, vol. 10, 2008.
- “A comprehensive approach for learning-based fully-automated inter-slice motion correction for short-axis cine cardiac mr image stacks,” ArXiv, vol. abs/1810.02201, 2018.
- “Automatic correction of motion artifacts in 4d left ventricle model reconstructed from mri,” in Computing in Cardiology 2014, 2014.
- “Correction of slice misalignment in multi-breath-hold cardiac mri scans,” in STACOM@MICCAI, 2016.
- “Correction of movement artifacts from 4-d cardiac short and long-axis mr data,” in International Conference on Medical Image Computing and Computer-Assisted Intervention, 2004.
- “Fully automated segmentation-based respiratory motion correction of multiplanar cardiac magnetic resonance images for large-scale datasets,” in International Conference on Medical Image Computing and Computer-Assisted Intervention, 2017.
- “3d motion modeling and reconstruction of left ventricle wall in cardiac mri,” Functional imaging and modeling of the heart (FIMH), 2017.
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