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.2025.2503023

Proceedings Articles

Power-Efficient Control of Non-Linear Magnetic Field Generators for MPI

Main Article Content

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

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

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

Abstract

The scaling of electrical power constitutes a significant challenge when adapting Magnetic Particle Imaging (MPI) to a human scale. The use of coils incorporating soft-iron cores serves to reduce power usage, but also introduces spatial imperfections and non-linearities in the current-to-field relationship. This study proposes methodologies for the control of the magnetic field output of a system comprising 18 coils, subject to the influence of saturated iron. In particular, we integrate current sequence optimization with neural network-based predictions for field and gradient values, thereby enabling the precise and power-optimal generation of magnetic fields. The proposed framework for controlling non-linear magnetic field generators represents a significant advancement in MPI technology, paving the way for the development of human-scale, power-efficient medical imaging solutions.

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