Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
369-05-005 ISMRM Abstract

Conditional Diffusion Model for Hyperpolarized 129Xe MR Image Generation Based on Mask-Guided Cross-Attention

Primary: Analysis Methods - Generative Models
Secondary: Analysis Methods - Data Processing
369-05-005 · Hyperpolarized Gases · Monday, 11 May, 4:10 PM–5:05 PM · Digital Posters Row J
Keywords: Hyperpolarized 129Xe MRI Synthetic data Conditional Diffusion model
Accepted
Muhong Li 1,2, Sa Xiao1, Linxuan Han1, Xin Zhou1
1State Key Laboratory of Magnetic Resonance Spectroscopy and Imaging, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, China
2School of Biomedical Engineering, Southern Medical University, Guangzhou，Guangdong, China
Presenting Author: Muhong Li

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References

1. Li H, Zhao X, Wang Y, et al. Damaged lung gas-exchange function of discharged COVID-19 patients detected by hyperpolarized 129Xe MRI. Sci Adv. 2021; 7:eabc8180. doi:10.1126/sciadv.abc8180 [doi]
2. Stock KW, Chen Q, Hatabu H, Edelman RR. Magnetic resonance T2* measurements of the normal human lung in vivo with ultra-short echo times. Magn Reson Imaging. 1999; 17(7):9971000.https://doi.org/10.1016/S0730-725X(99)00047-8 [doi]
3. Fan Y, Liao H, Huang S, et al. A survey of emerging applications of diffusion probabilistic models in MRI. Meta-Radiology. 2024;2(2):100082. https://doi.org/10.1016/j.metrad.2024.100082 [doi]
4. Pinaya W.H.L, Graham MS, et al. Fast Unsupervised Brain Anomaly Detection and Segmentation with Diffusion Models. 2022; 13438:705-714.https://doi.org/10.1007/978-3-031-16452-1_67 [doi]

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http://echo.ismrm.org/p/ISMRM2026/369-05-005