Efficient Image Registration Network for Non-Rigid Cardiac Motion Estimation
Pan J, Rueckert D, Kuestner T, Hammernik K (2021)
Publication Type: Conference contribution
Publication year: 2021
Journal
Publisher: Springer Science and Business Media Deutschland GmbH
Book Volume: 12964 LNCS
Pages Range: 14-24
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: Virtual, Online
ISBN: 9783030885519
DOI: 10.1007/978-3-030-88552-6_2
Abstract
Cardiac motion estimation plays an essential role in motion-compensated cardiac Magnetic Resonance (MR) image reconstruction. In this work, we propose a robust and lightweight self-supervised deep learning registration framework, termed MRAFT, to estimate non-rigid cardiac motion. The proposed framework combines an efficient architecture with a novel degradation-restoration (DR) loss term, and an enhancement mask derived from a pre-trained segmentation network. This framework enables the prediction of both small and large cardiac motion more precisely, and allows us to handle through-plane motion in a 2D registration setting via the DR loss. The quantitative and qualitative experiments on a retrospective cohort of 42 in-house acquired 2D cardiac CINE MRIs indicate that the proposed method outperforms the competing approaches substantially, with more than 25% reduction in residual photometric error, and up to 100 × faster inference speed compared to conventional methods.
Involved external institutions
Germany (DE)How to cite
APA:
Pan, J., Rueckert, D., Kuestner, T., & Hammernik, K. (2021). Efficient Image Registration Network for Non-Rigid Cardiac Motion Estimation. In Nandinee Haq, Patricia Johnson, Andreas Maier, Tobias Würfl, Jaejun Yoo (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 14-24). Virtual, Online: Springer Science and Business Media Deutschland GmbH.
MLA:
Pan, Jiazhen, et al. "Efficient Image Registration Network for Non-Rigid Cardiac Motion Estimation." Proceedings of the 4th International Workshop on Machine Learning for Medical Image Reconstruction, MLMIR 2021 held in Conjunction with 24th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2021, Virtual, Online Ed. Nandinee Haq, Patricia Johnson, Andreas Maier, Tobias Würfl, Jaejun Yoo, Springer Science and Business Media Deutschland GmbH, 2021. 14-24.
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