Power-efficient control of non-linear magnetic field generators for MPI

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.

DDC Class

621.3: Electrical Engineering, Electronic Engineering

004: Computer Sciences

530: Physics

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https://creativecommons.org/licenses/by/4.0/

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903.pdf

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770.35 KB

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Power-efficient control of non-linear magnetic field generators for MPI