Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
508-02-008 ISMRM Abstract

Joint Implicit Neural Representation for Fast Scan-Specific Magnetic Resonance Fingerprinting

Primary: Acquisition & Reconstruction - Image Reconstruction: AI
Secondary: Acquisition & Reconstruction - Quantitative Imaging: relaxometry, multi-parametric, MR Fingerprinting, and synthetic MRI
508-02-008 · Novel Reconstruction Techniques for Fast Imaging · Wednesday, 13 May, 8:20 AM–10:10 AM · Meeting Room 1.60
Keywords: MR Fingerprinting AI/ML Image Reconstruction Self-supevised learning Multiparametric magnetic resonance imaging Implicit Neural Representation
Accepted
Hongze Yu 1, Christopher Keen2, Kaixuan Jin1, Jeffrey A Fessler1,2,3, Yun Jiang2,3
1Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, United States of America
2Department of Biomedical Engineering, University of Michigan, Ann Arbor, United States of America
3Department of Radiology, University of Michigan, Ann Arbor, United States of America
Presenting Author: Hongze Yu

Synopsis

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References

1. D. Ma, V. Gulani, N. Seiberlich, K. Liu, J. L. Sunshine, J. L. Duerk, and M. A. Griswold, "Magnetic resonance fingerprinting," Nature, vol. 495, no. 7440, pp. 187–192, 2013. https://doi.org/10.1038/nature11971 [doi]
2. Y. Jiang, D. Ma, N. Seiberlich, V. Gulani, and M. A. Griswold, "MR fingerprinting using fast imaging with steady state precession (FISP) with spiral readout," Magnetic Resonance in Medicine, vol. 74, no. 6, pp. 1621–1631, 2015. https://doi.org/10.1002/mrm.25559 [doi]
3. G. Lima da Cruz, A. Bustin, O. Jaubert, T. Schneider, R. M. Botnar, and C. Prieto, “Sparsity and locally low rank regularization for MR fingerprinting,” Magnetic Resonance in Medicine, vol. 81, no. 6, pp. 3530–3543, 2019. https://doi.org/10.1002/mrm.27665 [doi]
4. J. I. Hamilton, “A self-supervised deep learning reconstruction for shortening the breathhold and acquisition window in cardiac magnetic resonance fingerprinting,” Frontiers in Cardiovascular Medicine, vol. 9, 2022, doi:10.3389/fcvm.2022.928546. [doi]
5. V. Sitzmann, J. N. P. Martel, A. W. Bergman, D. B. Lindell, and G. Wetzstein, "Implicit Neural Representations with Periodic Activation Functions," in Advances in Neural Information Processing Systems, vol. 33, pp. 7462–7473, 2020.
6. R. Feng, Q. Wu, J. Feng, H. She, C. Liu, Y. Zhang, and H. Wei, “IMJENSE: Scan-Specific Implicit Representation for Joint Coil Sensitivity and Image Estimation in Parallel MRI,” IEEE Transactions on Medical Imaging, vol. 43, no. 4, pp. 1539–1553, 2024. doi: 10.1109/TMI.2023.3342156 [doi]
7. J. Feng, R. Feng, Q. Wu, X. Shen, L. Chen, X. Li, L. Feng, J. Chen, Z. Zhang, C. Liu, Y. Zhang, and H. Wei, "Spatiotemporal Implicit Neural Representation for Unsupervised Dynamic MRI Reconstruction," IEEE Transactions on Medical Imaging, vol. 44, no. 5, pp. 2143–2156, 2025. doi: 10.1109/TMI.2025.3526452 [doi]
8. C. Li, J. Li, J. Zhang, E. Solomon, A. V. Dimov, P. Spincemaille, T. D. Nguyen, M. R. Prince, and Y. Wang, "Navigator motion-resolved MR fingerprinting using implicit neural representation: Feasibility for free-breathing three-dimensional whole-liver multiparametric mapping," Magnetic Resonance in Medicine, 2025, advance online publication. doi: 10.1002/mrm.70063 [doi]
9. H. Yu, J. A. Fessler, and Y. Jiang, "Bilevel Optimized Implicit Neural Representation for Scan-Specific Accelerated MRI Reconstruction," arXiv preprint arXiv:2502.21292, January 2025.
10. D. F. McGivney, E. Pierre, D. Ma, Y. Jiang, H. Saybasili, V. Gulani, and M. A. Griswold, "SVD Compression for Magnetic Resonance Fingerprinting in the Time Domain," IEEE Transactions on Medical Imaging, vol. 33, no. 12, pp. 2311–2322, 2014. https://doi.org/10.1109/TMI.2014.2337321 [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/508-02-008