Quality-Enhancing Techniques for Model-Based Reconstruction in Magnetic Particle Imaging

Vladyslav Gapyak (), Thomas März and Andreas Weinmann
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Vladyslav Gapyak: Hochschule Darmstadt, Schöfferstraße 3, 64295 Darmstadt, Germany
Thomas März: Hochschule Darmstadt, Schöfferstraße 3, 64295 Darmstadt, Germany
Andreas Weinmann: Hochschule Darmstadt, Schöfferstraße 3, 64295 Darmstadt, Germany

Mathematics, 2022, vol. 10, issue 18, 1-22

Abstract: Magnetic Particle Imaging is an imaging modality that exploits the non-linear magnetization response of superparamagnetic nanoparticles to a dynamic magnetic field. In the multivariate case, measurement-based reconstruction approaches are common and involve a system matrix whose acquisition is time consuming and needs to be repeated whenever the scanning setup changes. Our approach relies on reconstruction formulae derived from a mathematical model of the MPI signal encoding. A particular feature of the reconstruction formulae and the corresponding algorithms is that these are independent of the particular scanning trajectories. In this paper, we present basic ways of leveraging this independence property to enhance the quality of the reconstruction by merging data from different scans. In particular, we show how to combine scans of the same specimen under different rotation angles. We demonstrate the potential of the proposed techniques with numerical experiments.

Keywords: magnetic particle imaging; model-based reconstruction; total variation; phase space; inverse problems (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
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