International Journal on Magnetic Particle Imaging IJMPI
Vol. 12 No. 1 Suppl 1 (2026): Int J Mag Part Imag
https://doi.org/10.18416/IJMPI.2026.2603044

Proceedings Articles, ID 936

Randomized Greedy Kaczmarz for Multi-Contrast Magnetic Particle Imaging

Main Article Content

Niklas Hackelberg (1) Fraunhofer Research Institution for Individualized and Cell-based Medical Engineering IMTE; 2) Institute for Biomedical Imaging, Hamburg University of Technology), Patricia Römer (Fraunhofer Research Institution for Individualized and Cell-based Medical Engineering IMTE), Kolya Ruppel (Institute for Biomedical Imaging, Hamburg University of Technology), Lina Nawwas (1) Institute for Biomedical Imaging, Hamburg University of Technology; 2) Section for Biomedical Imaging, University Medical Center Hamburg-Eppendorf), Martin Möddel (1) Institute for Biomedical Imaging, Hamburg University of Technology; 2) Section for Biomedical Imaging, University Medical Center Hamburg-Eppendorf), Marija Boberg (1) Institute for Biomedical Imaging, Hamburg University of Technology; 2) Section for Biomedical Imaging, University Medical Center Hamburg-Eppendorf), Tobias Knopp (1) Fraunhofer Research Institution for Individualized and Cell-based Medical Engineering IMTE; 2) Institute for Biomedical Imaging, Hamburg University of Technology; 3) Section for Biomedical Imaging, University Medical Center Hamburg-Eppendorf)

Copyright (c) 2026 Niklas Hackelberg, Patricia Römer, Kolya Ruppel, Lina Nawwas, Martin Möddel, Marija Boberg, Tobias Knopp

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This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Multi-contrast magnetic particle imaging allows for separating signals from different tracer materials or microenvironments
from one joint measurement, yielding multi-channel images that distinguish tracers or encode properties
such as temperature or viscosity. However, leakage artifacts enforce a noticeably longer application of iterative
standard methods like the Kaczmarz algorithm to reach satisfactory reconstruction results. A greedy randomized
version of the Kaczmarz method is adapted, showing the potential for faster recovery.

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