Towards Accurate Modeling of the Multidimensional Magnetic Particle Imaging Physics

TL;DR

This paper introduces a new physical model based on Néel rotation for magnetic particle imaging that accurately describes nanoparticle magnetization, reducing calibration time and improving image reconstruction quality.

Contribution

The work presents a novel Néel rotation-based physical model that outperforms existing models in describing MPI data and eliminates the need for extensive system matrix calibration.

Findings

Model parameters fit measured data with higher precision.

Simulated system matrix reduces artifacts in reconstructed images.

Model enables accurate image reconstruction without calibration.

Abstract

The image reconstruction problem of the tomographic imaging technique magnetic particle imaging (MPI) requires the solution of a linear inverse problem. One prerequisite for this task is that the imaging operator that describes the mapping between the tomographic image and the measured signal is accurately known. For 2D and 3D excitation patterns, it is common to measure the system matrix in a calibration procedure, that is both, very time consuming and adds noise to the operator. The need for measuring the system matrix is due to the lack of an accurate physical model that is capable of describing the nanoparticles' magnetization behavior. Within this work we introduce a physical model that is based on N\'{e}el rotation for large particle ensembles and we find model parameters that describe measured 2D MPI data with much higher precision than state of the art MPI models. With phantom experiments we show that the simulated system matrix can be used for image reconstruction and reduces artifacts due to model-mismatch considerably.