Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
507-02-006 ISMRM Abstract

Quantitative MRI Mapping using Diffusion Models with Data Consistency on 3D Fast Zero Echo Time Acquisition

Accepted
Shishuai Wang 1, Florian Wiesinger2, Noemi Sgambelluri1, Carolin Pirkl2, Stefan Klein1, juan hernandez tamames1, Dirk H. J. Poot1
1Erasmus MC, Rotterdam, Netherlands
2GE Healthcare, Munich, Germany
Presenting Author: Shishuai Wang

Synopsis

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References

1. Ho J, Jain A, Abbeel P. Denoising diffusion probabilistic models. Advances in neural information processing systems. 2020;33:6840-51.
2. Ljungberg E, Damestani NL, Wood TC, Lythgoe DJ, Zelaya F, Williams SC, et al. Silent zero TE MR neuroimaging: current state-of-the-art and future directions. Prog Nucl Magn Reson Spectrosc. 2021;123:73-93. doi:10.1016/j.pnmrs.2021.03.002 [doi]
3. Wiesinger F, McKinnon G, Kaushik S, Solana AB, Ljungberg E, Vogel M, et al. 3D Silent parameter mapping: Further refinements & quantitative assessment. In: Proceedings of the Annual Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM). 2021.
4. Wiesinger F, Ljungberg E, Engström M, Kaushik S, Wood T, Williams S, et al. PSST… Parameter mapping Swift and SilenT. In: Proceedings of the Annual Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM). 2020.
5. Wang S, Ma H, Hernandez-Tamames JA, Klein S, Poot DH. qMRI diffuser: quantitative T1 mapping of the brain using a denoising diffusion probabilistic model. MICCAI Workshop on Deep Generative Models; 2024. doi: 10.1007/978-3-031-72744-3_13 [doi]
6. Song B, Kwon SM, Zhang Z, Hu X, Qu Q, Shen L. Solving inverse problems with latent diffusion models via hard data consistency. arXiv preprint arXiv:230708123. 2023.
7. Cocosco CA, Kollokian V, Kwan RKS, Evans AC. BrainWeb: Online interface to a 3D MRI simulated brain database. NeuroImage. 1997.

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