Patryk Szwargulski, M.Sc.

Universitätsklinikum Hamburg-Eppendorf (UKE)
Sektion für Biomedizinische Bildgebung
Lottestraße 55
2ter Stock, Raum 203
22529 Hamburg

Technische Universität Hamburg (TUHH)
Institut für Biomedizinische Bildgebung
Gebäude E, Raum 4.044
Am Schwarzenberg-Campus 3
21073 Hamburg

Tel.: 040 / 7410 56309
E-Mail: p.szwargulski(at)uke.de
E-Mail: patryk.szwargulski(at)tuhh.de

Research Interests

  • Magnetic Particle Imaging
  • Image Reconstruction
  • Signal and Image Processing

Curriculum Vitae

In 2015 Patryk Szwargulski graduated with a master's degree thesis on Fast Reconstruction of Magnetic Particle Imaging Data using the Focusfields. Currently he is a PhD student in the group of Tobias Knopp for experimental Biomedical Imaging at the University Medical Center Hamburg-Eppendorf and the Hamburg University of Technology.

Publications

[134633]
Title: Towards accurate modeling of the multidimensional magnetic particle imaging physics
Written by: T. Kluth, P. Szwargulski, T. Knopp
in: New Journal of Physics 10 2019
Volume: 21 Number: 10
on pages: 103032
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DOI: 10.1088/1367-2630/ab4938
URL: https://doi.org/10.1088%2F1367-2630%2Fab4938
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Note: article

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 model that is capable of describing the nanoparticles’ magnetization behavior in the MPI setup. Within this work we exploit a physical model that is based on Néel 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.