Low-rank based motion correction followed by automatic frame selection in diffusion tensor CMR

Motivation: Post-processing of in-vivo diffusion tensor CMR (DT-CMR) is challenging due to the low SNR and variation in contrast between frames which makes image registration difficult, and the need to manually reject frames corrupted by motion. Goal(s): To develop a semi-automatic post-processing pipeline for robust DT-CMR registration and automatic frame selection. Approach: We used low intrinsic rank averaged frames as the reference to register other low-ranked frames. A myocardium-guided frame selection rejected the frames with signal loss, through-plane motion and poor registration. Results: The proposed method outperformed our previous noise-robust rigid registration on helix angle data quality and reduced negative eigenvalues in healthy volunteers. Impact: This improved image registration and frame selection algorithm may enable groupwise deformable registration on DT-CMR, paving the way towards clinical translation.

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Publication Details

Journal
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Published
2024-11-26
DOI
https://doi.org/10.58530/2024/2141
Primary Topic
Advanced Neuroimaging Techniques and Applications
Type
article
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article

Low-rank based motion correction followed by automatic frame selection in diffusion tensor CMR

Fanwen Wang, Camila Muñoz, Yinzhe Wu, Yaqing Luo et al.
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Advanced Neuroimaging Techniques and Applications
article

Low-rank based motion correction followed by automatic frame selection in diffusion tensor CMR

Fanwen Wang, Camila Muñoz, Yinzhe Wu, Yaqing Luo, Andrew Mark Scott, Sònia Nielles‐Vallespin, Pedro G. Ferreira, Dudley J. Pennell, Guang Yang, Ke Wen, Jiahao Huang
article en

Abstract

Motivation: Post-processing of in-vivo diffusion tensor CMR (DT-CMR) is challenging due to the low SNR and variation in contrast between frames which makes image registration difficult, and the need to manually reject frames corrupted by motion. Goal(s): To develop a semi-automatic post-processing pipeline for robust DT-CMR registration and automatic frame selection. Approach: We used low intrinsic rank averaged frames as the reference to register other low-ranked frames. A myocardium-guided frame selection rejected the frames with signal loss, through-plane motion and poor registration. Results: The proposed method outperformed our previous noise-robust rigid registration on helix angle data quality and reduced negative eigenvalues in healthy volunteers. Impact: This improved image registration and frame selection algorithm may enable groupwise deformable registration on DT-CMR, paving the way towards clinical translation.

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
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Openalex Percentile: Top 64%
Advanced Neuroimaging Techniques and Applications
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