Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
430-03-004 ISMRM Abstract

Water Content Guided Physics-Informed Neural Networks for Enhanced Magnetic Resonance Electrical Properties Tomography

Primary: Physics & Engineering - Bioeffects & Magnetic Fields
Secondary: Acquisition & Reconstruction - Image Reconstruction: AI
430-03-004 · Advanced Image Reconstruction · Tuesday, 12 May, 1:40 PM–3:30 PM · Meeting Room 2.60
Keywords: Physics-informed Neural Networks Electrical Properties Tomography Water Content
Accepted
Yaqing Jia 1, Chunyou Ye1, Yikun Hong1, Yunyu Gao2, Yanming Wang3, BenSheng Qiu3, Xiang Nan4, Jijun Han1
1School of Biomedical Engineering, Anhui Medical University, Hefei, China
2Clinical and Technical Support, Philips Healthcare (Guangzhou), Guangzhou, China
3Medical Imaging Center, Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, China
4Basic Medical School, Anhui Medical University, Hefei, China
Presenting Author: Yaqing Jia

Synopsis

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References

1. Haacke E M, Petropoulos L S, Nilges E W, et al. Extraction of conductivity and permittivity using magnetic resonance imaging. Physics in Medicine & Biology, 1991; 36(6): 723. doi: 10.1088/0031-9155/36/6/002 [doi]
2. Gurler N, Ider Y Z. Gradient‐based electrical conductivity imaging using MR phase. Magnetic Resonance in Medicine, 2017; 77(1): 137-150. doi: 10.1002/mrm.26097 [doi]
3. Lee J, Shin J, Kim D H. MR‐based conductivity imaging using multiple receiver coils. Magnetic Resonance in Medicine, 2016; 76(2): 530-539. doi: 10.1002/mrm.25891 [doi]
4. Borsic A, Perreard I, Mahara A, et al. An inverse problems approach to MR-EPT image reconstruction. IEEE transactions on medical imaging, 2015; 35(1): 244-256. doi: 10.1109/TMI.2015.2466082 [doi]
5. Michel E, Hernandez D, Lee S Y. Electrical conductivity and permittivity maps of brain tissues derived from water content based on T1‐weighted acquisition. Magnetic Resonance in Medicine, 2017; 77(3): 1094-1103. doi: 10.1002/mrm.26193 [doi]
6. Ruan G, Wang Z, Liu C, et al. Magnetic resonance electrical properties tomography based on modified physics-informed neural network and multiconstraints. IEEE Transactions on Medical Imaging, 2024; 43(9): 3263-3278. doi: 10.1109/TMI.2024.3391651 [doi]
7. Meerbothe T G, Meliado E F, Stijnman P R S, et al. A database for MR‐based electrical properties tomography with in silico brain data—ADEPT. Magnetic Resonance in Medicine, 2024; 91(3): 1190-1199. doi: 10.1002/mrm.29904 [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/430-03-004