Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
662-04-007 ISMRM Abstract

Accelerated Abdominal MRI at 0.05 Tesla via Golden-angle Radial Sampling and Deep Learning Reconstruction

Primary: Body - Liver
Secondary: Physics & Engineering - Low-Field MRI
662-04-007 · Artificial Intelligence-Based Image Reconstruction in the Body · Thursday, 14 May, 2:35 PM–3:30 PM · Digital Posters Row C
Keywords: Deep learning reconstruction Abdominal MRI Golden-angle radial sampling
Accepted
Junhao Zhang1,2, Yujiao Zhao1,2, Vick Lau1,2, Xiang Li1,2, Jiahao Hu1,2, Shi Su1,2, Ye Ding1,2, Alex T. L. Leong 1,2, Ed X Wu1,2
1Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Hong Kong, China
2Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, China
Presenting Author: Alex T. L. Leong

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. Feng L, Chandarana H. Accelerated Abdominal MRI: A Review of Current Methods and Applications. Journal of Magnetic Resonance Imaging 2025.
2. Niu Z, Zhong G, Yu H. A review on the attention mechanism of deep learning. Neurocomputing 2021;452:48-62.
3. Zhang K, Zuo W, Chen Y, Meng D, Zhang L. Beyond a gaussian denoiser: Residual learning of deep cnn for image denoising. IEEE Transactions on Image Processing 2017;26(7):3142-3155.
4. Feng L, Grimm R, Block KT, Chandarana H, Kim S, Xu J, Axel L, Sodickson DK, Otazo R. Golden‐angle radial sparse parallel MRI: combination of compressed sensing, parallel imaging, and golden‐angle radial sampling for fast and flexible dynamic volumetric MRI. Magnetic resonance in medicine 2014;72(3):707-717.
5. Zhao Y, Ding Y, Lau V, Man C, Su S, Xiao L, Leong AT, Wu EX. Whole-body magnetic resonance imaging at 0.05 Tesla. Science 2024;384(6696):eadm7168.
6. Man C, Lau V, Su S, Zhao Y, Xiao L, Ding Y, Leung GK, Leong AT, Wu EX. Deep learning enabled fast 3D brain MRI at 0.055 tesla. Science Advances 2023;9(38):eadi9327.
7. Lau V, Xiao L, Zhao Y, Su S, Ding Y, Man C, Wang X, Tsang A, Cao P, Lau GK. Pushing the limits of low‐cost ultra‐low‐field MRI by dual‐acquisition deep learning 3D superresolution. Magnetic resonance in medicine 2023;90(2):400-416.
8. Liu Y, Leong AT, Zhao Y, Xiao L, Mak HK, Tsang ACO, Lau GK, Leung GK, Wu EX. A low-cost and shielding-free ultra-low-field brain MRI scanner. Nature Communications 2021;12(1):7238.
9. Zhao Y, Xiao L, Liu Y, Leong AT, Wu EX. Electromagnetic interference elimination via active sensing and deep learning prediction for radiofrequency shielding‐free MRI. NMR in Biomedicine 2024;37(7):e4956.
10. McGibney G, Smith M, Nichols S, Crawley A. Quantitative evaluation of several partial Fourier reconstruction algorithms used in MRI. Magnetic resonance in medicine 1993;30(1):51-59.
11. Zhang Z. Improved adam optimizer for deep neural networks. In: 2018 IEEE/ACM 26th international symposium on quality of service (IWQoS), 2018, Ieee, p 1-2.
12. Kazerouni A, Aghdam EK, Heidari M, Azad R, Fayyaz M, Hacihaliloglu I, Merhof D. Diffusion models for medical image analysis: A comprehensive survey. arXiv preprint arXiv:221107804 2022.
13. Guo P, Mei Y, Zhou J, Jiang S, Patel VM. Reconformer: Accelerated mri reconstruction using recurrent transformer. IEEE transactions on medical imaging 2023;43(1):582-593.

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/662-04-007