Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
368-01-011 ISMRM Abstract

Joint Optimization of Acquisition, Reconstruction, and Registration for Maximizing Motion Estimation in Dynamic Cardiac MRI

Primary: Acquisition & Reconstruction - AI methods
Secondary: Analysis Methods - Image Registration and Alignment
368-01-011 · Registration, Atlases, and Motion · Monday, 11 May, 8:20 AM–9:15 AM · Digital Posters Row I
Keywords: AI/ML Image Reconstruction Image registration Sampling pattern optimization Joint Reconstruction Dynamic MRI Reconstruction
Accepted
George Yiasemis 1,2, Jan-Jakob Sonke1,2, Jonas Teuwen1,2
1the Netherlands Cancer Institute, Amsterdam, Netherlands
2University of Amsterdam, Amsterdam, Netherlands
Presenting Author: George Yiasemis

Synopsis

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References

1. Yiasemis, G., Sonke, J. J., & Teuwen, J. (2024). End-to-end adaptive dynamic subsampling and reconstruction for cardiac mri. arXiv preprint arXiv:2403.10346. doi: https://doi.org/10.48550/arXiv.2403.10346. [doi]
2. Yiasemis, G., Moriakov, N., Sonke, J. J., & Teuwen, J. (2025). vSHARP: Variable Splitting Half-quadratic ADMM algorithm for reconstruction of inverse-problems. Magnetic Resonance Imaging, 115, 110266. doi: https://doi.org/10.1016/j.mri.2024.110266. [doi]
3. Balakrishnan, G., Zhao, A., Sabuncu, M. R., Guttag, J., & Dalca, A. V. (2019). Voxelmorph: learning framework for deformable medical image registration. IEEE transactions on medical imaging, 38(8), 1788-1800. doi: 10.1109/TMI.2019.2897538. [doi]
4. Wang, C., Lyu, J., Wang, S., Qin, C., Guo, K., Zhang, X., ... & Qu, X. (2024). CMRxRecon: A publicly available k-space dataset and benchmark to advance deep learning for cardiac MRI. Scientific Data, 11(1), 687. doi: https://doi.org/10.1038/s41597-024-03525-4. [doi]
5. Wang, Z., Wang, F., Qin, C., Lyu, J., Ouyang, C., Wang, S., ... & Wang, C. (2025). Cmrxrecon2024: A multimodality, multiview k-space dataset boosting universal machine learning for accelerated cardiac mri. Radiology: Artificial Intelligence, 7(2), e240443. doi: https://doi.org/10.1148/ryai.240443. [doi]
6. Vercauteren, T., Pennec, X., Perchant, A., & Ayache, N. (2009). Diffeomorphic demons: Efficient non-parametric image registration. NeuroImage, 45(1), S61-S72. doi: https://doi.org/10.1016/j.neuroimage.2008.10.040. [doi]
7. Chen, J., Frey, E. C., He, Y., Segars, W. P., Li, Y., & Du, Y. (2022). Transmorph: Transformer for unsupervised medical image registration. Medical image analysis, 82, 102615. doi: https://doi.org/10.1016/j.media.2022.102615. [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/368-01-011