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

Fanwen Wang; Pedro F. Ferreira; Camila Munoz; Ke Wen; Yaqing Luo; Jiahao Huang; Yinzhe Wu; Dudley J. Pennell; Andrew D. Scott; Sonia Nielles-Vallespin; Guang Yang

arXiv · 2406.13708

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

Fanwen Wang·Pedro F. Ferreira·Camila Munoz·Ke Wen·Yaqing Luo·Jiahao Huang·Yinzhe Wu·Dudley J. Pennell·Andrew D. Scott·Sonia Nielles-Vallespin·Guang Yang

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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. Goals: 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.

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Fanwen Wang, Pedro F. Ferreira, Camila Munoz, Ke Wen, Yaqing Luo, Jiahao Huang, Yinzhe Wu, Dudley J. Pennell, Andrew D. Scott, Sonia Nielles-Vallespin, Guang Yang. 2024-06-19. Low-rank based motion correction followed by automatic frame selection in DT-CMR. https://arxiv.org/abs/2406.13708

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