Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
660-04-003 ISMRM Abstract

Rethinking zero-shot self-supervised learning for MRI reconstruction

Primary: Acquisition & Reconstruction - Image Reconstruction: AI
Secondary: Acquisition & Reconstruction - AI methods
660-04-003 · AI: Anything Synthetic or Correcting Artifacts · Thursday, 14 May, 2:35 PM–3:30 PM · Digital Posters Row A
Keywords: Physics-guided deep learning MRI Reconstruction Self-supervised learning Zero shot self supervised learning
Accepted
Wenlei Shang1, Wenjian Liu 1, Zijian Zhou1, Peng Hu1,2,3
1School of Biomedical Engineering, ShanghaiTech University, Shanghai, China
2Shanghai Clinical Research and Trial Center, ShanghaiTech University, shanghai, China
3State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai, China
Presenting Author: Wenjian Liu

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References

1. Yaman, Burhaneddin, Seyed Amir Hossein Hosseini, and Mehmet Akçakaya. "Zero-shot self-supervised learning for MRI reconstruction." arXiv preprint arXiv:2102.07737 (2021).
2. Joo, Jinho, et al. "AeSPa: Attention-guided Self-supervised Parallel Imaging for MRI Reconstruction." Proceedings of the Computer Vision and Pattern Recognition Conference. 2025.
3. Mansour, Youssef, and Reinhard Heckel. "Zero-shot noise2noise: Efficient image denoising without any data." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2023. doi: 10.1109/CVPR52729.2023.01347. [doi]
4. Yaman, Burhaneddin, et al. "Self‐supervised learning of physics‐guided reconstruction neural networks without fully sampled reference data." Magnetic resonance in medicine 84.6 (2020): 3172-3191.. doi: 10.1002/mrm.28378. Epub 2020 Jul 2. PMID: 32614100; PMCID: PMC7811359. [doi] [pmid]
5. Tachella, Julián, Dongdong Chen, and Mike Davies. "Unsupervised learning from incomplete measurements for inverse problems." Advances in Neural Information Processing Systems 35 (2022): 4983-4995.
6. Darestani, Mohammad Zalbagi, and Reinhard Heckel. "Accelerated MRI with un-trained neural networks." IEEE Transactions on Computational Imaging 7 (2021): 724-733. doi: 10.1109/TCI.2021.3097596. [doi]
7. Desai, Arjun D., et al. "Noise2Recon: enabling SNR‐robust MRI reconstruction with semi‐supervised and self‐supervised learning." Magnetic Resonance in Medicine 90.5 (2023): 2052-2070.. doi:10.1002/mrm.29759 [doi]
8. Ulyanov, Dmitry, Andrea Vedaldi, and Victor Lempitsky. "Deep image prior." Proceedings of the IEEE conference on computer vision and pattern recognition. 2018.
9. Bell, Evan, et al. "Robust self-guided deep image prior." ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2023. doi: 10.1109/ICASSP49357.2023.10096631. [doi]
10. Knoll F, Zbontar J, Sriram A, Muckley MJ, Bruno M, Defazio A, Parente M, Geras KJ, Katsnelson J, Chandarana H, Zhang Z, Drozdzalv M, Romero A, Rabbat M, Vincent P, Pinkerton J, Wang D, Yakubova N, Owens E, Zitnick CL, Recht MP, Sodickson DK, Lui YW. fastMRI: A Publicly Available Raw k-Space and DICOM Dataset of Knee Images for Accelerated MR Image Reconstruction Using Machine Learning. Radiol Artif Intell. 2020 Jan 29;2(1):e190007. doi: 10.1148/ryai.2020190007. PMID: 32076662; PMCID: PMC6996599. [doi] [pmid]

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http://echo.ismrm.org/p/ISMRM2026/660-04-003