Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
661-03-001 ISMRM Abstract

Shuffled Repetition-to-Repetition Learning (Rep2Rep-Shuffle) for Noise-Adaptive Self-Supervised Denoising in Sodium MRI

Primary: Acquisition & Reconstruction - AI methods
Secondary: Contrast Mechanisms - Non-Proton
661-03-001 · Noise and Artifact Mitigation in MRI · Thursday, 14 May, 1:40 PM–2:35 PM · Digital Posters Row B
Keywords: Sodium MRI Data Augmentation Noise-adaptive Self-supervised denoising LIMITED DATA
Accepted
Renqing Luo1,2,3, Nikola P Janjusevic 1,2, Haoyang Pei1,2,3, Yao Wang3, Guillaume Madelin1,2, Li Feng1,2
1Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, New York, United States of America
2Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University Grossman School of Medicine, New York, United States of America
3NYU Tandon School of Engineering, New York, United States of America
Presenting Author: Nikola P Janjusevic

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References

1. Janjušević, N., Chen, J., Ginocchio, L., Bruno, M., Huang, Y., Wang, Y., Chandarana, H., & Feng, L. (2025). Self-supervised noise adaptive MRI denoising via Repetition to Repetition (Rep2Rep) learning. Magnetic Resonance in Medicine.
2. Janjušević, N., Chen, J., Ginocchio, L., Bruno, M., Huang, Y., Wang, Y., ... & Feng, L. (2025). Self-Supervised Noise Adaptive MRI Denoising via Repetition to Repetition (Rep2Rep) Learning. arXiv preprint arXiv:2504.17698.
3. Lehtinen, J., Munkberg, J., Hasselgren, J., Laine, S., Karras, T., Aittala, M., & Aila, T. (2018). Noise2Noise: Learning image restoration without clean data. arXiv preprint arXiv:1803.04189.
4. Madelin, G., & Regatte, R. R. (2013). Biomedical applications of sodium MRI in vivo. Journal of magnetic resonance imaging : JMRI, 38(3), 511–529. https://doi.org/10.1002/jmri.24168 [doi]
5. Nunes Neto, L. P., Madelin, G., Sood, T. P., Wu, C. C., Kondziolka, D., Placantonakis, D., Golfinos, J. G., Chi, A., & Jain, R. (2018). Quantitative sodium imaging and gliomas: a feasibility study. Neuroradiology, 60(8), 795–802. https://doi.org/10.1007/s00234-018-2041-1 [doi]
6. Janjusevic, Nikola & Khalilian-Gourtani, Amirhossein & Wang, Yao. (2022). CDLNet: Noise-Adaptive Convolutional Dictionary Learning Network for Blind Denoising and Demosaicing. IEEE Open Journal of Signal Processing. 3. 1-1. 10.1109/OJSP.2022.3172842. [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/661-03-001