A model-based reconstruction approach to field-free line magnetic particle imaging

Magnetic particle imaging (MPI) visualizes the spatial distribution of superparamagnetic iron oxide nanoparticles by exploiting their nonlinear magnetization response to time-varying magnetic fields. In open-sided MPI scanners using a field-free line (FFL), tomographic imaging is achieved by rotating the FFL and reconstructing from angledependent projections. At low tracer concentrations, the induced voltage signal has reduced signal-to-noise ratio resulting in pronounced reconstruction artifacts. The ISBI2026 low-concentration MPI reconstruction challenge aims to address this problem by providing a dataset of high- and low-concentration samples. This paper describes a solution to this challenge. We propose a two-stage pipeline: a simulated system matrix based on an equilibrium Langevin forward model is used to recover sinograms followed by iterative image reconstruction. Despite limited system information, the approach yields competitive reconstructions, though remaining artifacts and moderate similarity metrics indicate a high potential for improvement.

Subjects

field-free line scanner

low concentration

Magnetic particle imaging

reconstruction

DDC Class

600: Technology

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A model-based reconstruction approach to field-free line magnetic particle imaging