International Journal on Magnetic Particle Imaging IJMPI
Vol. 11 No. 1 Suppl 1 (2025): Int J Mag Part Imag
https://doi.org/10.18416/IJMPI.2025.2503009

Proceedings Articles

Current-to-Field Prediction for Non-Linear Magnetic Systems via Neural Networks

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Fynn Foerger (1) Section for Biomedical Imaging, University Medical Center Hamburg-Eppendorf, Hamburg, Germany 2) Institute for Biomedical Imaging, Hamburg University of Technology, Hamburg, Germany), Paul Jürß (1) Section for Biomedical Imaging, University Medical Center Hamburg-Eppendorf, Hamburg, Germany 2) Institute for Biomedical Imaging, Hamburg University of Technology, Hamburg, Germany), Marija Boberg (1) Section for Biomedical Imaging, University Medical Center Hamburg-Eppendorf, Hamburg, Germany 2) Institute for Biomedical Imaging, Hamburg University of Technology, Hamburg, Germany), Tim Hau (1) Institute for Biomedical Imaging, Hamburg University of Technology, Hamburg, Germany), Tobias Knopp (1) Section for Biomedical Imaging, University Medical Center Hamburg-Eppendorf, Hamburg, Germany 2) Institute for Biomedical Imaging, Hamburg University of Technology, Hamburg, Germany 3) Fraunhofer Research Institution for Individualized and Cell-based Medical Engineering IMTE, Lübeck, Germany), Martin Möddel (1) Section for Biomedical Imaging, University Medical Center Hamburg-Eppendorf, Hamburg, Germany 2) Institute for Biomedical Imaging, Hamburg University of Technology, Hamburg, Germany)

Copyright (c) 2025 Fynn Foerger, Paul Jürß, Marija Boberg, Tim Hau, Tobias Knopp, Martin Möddel

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This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Accurate magnetic field knowledge is crucial for magnetic particle imaging, affecting performance estimation, sequence generation, and reconstruction. Especially for non-linear field generators, such as those with built-in soft iron, conventional field simulations, such as the finite element method, are computationally demanding. We propose the use of neural networks to predict the coefficients of the spherical harmonic expansions of the fields from the input currents, drastically speeding up current-to-field prediction.

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