MNP characterization and signal prediction using a model-based dictionary

Abstract

Magnetic Particle Imaging (MPI) utilizes the nonlinear magnetic response of magnetic nanoparticles (MNPs) for signal localization. Accurate modeling of the magnetization behavior of MNPs is crucial for understanding their MPI signal responses. In this work, we propose a model-based dictionary approach using a coupled Brown-Néel rotation model. With experimental results on a Magnetic Particle Spectrometer (MPS), we show that this approach can successfully characterize MNPs and predict their signal responses.