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.
@article{arxiv.2406.13708,
title = {Low-rank based motion correction followed by automatic frame selection in DT-CMR},
author = {Fanwen Wang and Pedro F. Ferreira and Camila Munoz and Ke Wen and Yaqing Luo and Jiahao Huang and Yinzhe Wu and Dudley J. Pennell and Andrew D. Scott and Sonia Nielles-Vallespin and Guang Yang},
journal= {arXiv preprint arXiv:2406.13708},
year = {2024}
}