Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
463-01-014 ISMRM Abstract

Uncertainty-Aware Cross-Modal MRI Reconstruction via Evidential Beta-Gated Attention

Primary: Acquisition & Reconstruction - Image Reconstruction: AI
Secondary: Acquisition & Reconstruction - AI methods
463-01-014 · Data-Driven Reconstruction: From Networks to Clinical Practice · Tuesday, 12 May, 8:20 AM–9:15 AM · Digital Posters Row D
Keywords: MRI Reconstruction Evidential Deep Learning Text-Guided Imaging
Accepted
Bingbing Chen 1, Congcong Liu2,3,4, Yihang Zhou3,4,5,6, Zhuoxu Cui4,5,6, Dong Liang2,3,4,5,6,7,8
1School of Biomedical Engineering, ShanghaiTech University, Shanghai, China
2Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
3Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
4Research Center for Medical AI, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
5University of Chinese Academy of Sciences, Beijing, China
6State Key Laboratory of Biomedical Imaging Science and System, Shenzhen, China
7State Key Laboratory of Biomedical Imaging Science and System, Key Laboratory of Biomedical Imaging Science and System, Chinese Academy of Sciences, Shenzhen, China
8Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
Presenting Author: Bingbing Chen

Synopsis

Motivation:
Goals:
Approach:
Results:
Full abstract & presentation

The full text, figures, and any recorded presentation for this abstract are not shown here. Log in if you are a member or registered attendee with access.

Full abstracts, figures, and presentations for Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition are available to registered attendees. This content becomes freely available to the public roughly two years after the meeting.

To request or purchase access, contact the ISMRM Central Office at info@ismrm.org.

Log in

References

1. Zhang, Lvmin, Anyi Rao, and Maneesh Agrawala. "Adding conditional control to text-to-image diffusion models." Proceedings of the IEEE/CVF International Conference on Computer Vision. 2023.
2. Jiang, Lan, et al. "Cola-diff: Conditional latent diffusion model for multi-modal mri synthesis." International Conference on Medical Image Computing and Computer-Assisted Intervention. Cham: Springer Nature Switzerland, 2023.
3. Cui, Zhuo-Xu, et al. "Spirit-diffusion: Self-consistency driven diffusion model for accelerated mri." IEEE Transactions on Medical Imaging (2024).
4. Chung, Hyungjin, et al. "Contextmri: Enhancing compressed sensing MRI through metadata conditioning." arXiv preprint arXiv:2501.04284 (2025).
5. Sensoy, Murat, Lance Kaplan, and Melih Kandemir. "Evidential deep learning to quantify classification uncertainty." Advances in neural information processing systems 31 (2018).

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/463-01-014