Paul Jürß, M.Sc.

profile picture of Paul Jürß

Universitätsklinikum Hamburg-Eppendorf (UKE)
Sektion für Biomedizinische Bildgebung
Lottestraße 55
2ter Stock, Raum 210
22529 Hamburg

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

Tel.: 040 / 7410 25811
E-Mail: paul.juerss(at)tuhh.de
E-Mail: p.juerss(at)uke.de
ORCID: https://orcid.org/0000-0002-3475-8480

Research Interests

  • Image Reconstruction
  • Machine Learning

Curriculum Vitae

Paul Jürß is a PhD student in the group of Tobias Knopp for Biomedical Imaging at the University Medical Center Hamburg-Eppendorf and the Hamburg University of Technology. In 2020, he graduated with a bachelor's degree in Computer Science in Engineering at the Hamburg University of Technology. From 2020 to 2022, he studied Technomathematics at the University of Hamburg and obtained his master's degree with a thesis on "Compensation of motion artifacts in HR-pQCT".

Conference Proceedings

[191963]
Title: Uncertainties of a Spherical Magnetic Field Camera.
Written by: F. Foerger, P. Suskin, M. Boberg, J. Faltinath, T. Knopp and M. Möddel
in: <em>2025 IEEE SENSORS</em>. (2025).
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on pages: 1-4
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DOI: https://doi.org/10.1109/SENSORS59705.2025.11331079
URL: https://ieeexplore.ieee.org/document/11331079
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Note: inproceedings

Abstract: Spherical harmonic expansions are well-established tools for estimating magnetic fields from surface measurements and are widely used in applications such as tomographic imaging, geomagnetism, and biomagnetism. Although the mathematical foundations of these expansions are well understood, the impact of real-world imperfections, on the uncertainty of the field model has received little attention. In this work, we present a systematic uncertainty propagation analysis for a magnetic field camera that estimates the field from surface measurements using a spherical array of Hall magnetometers arranged in a spherical t-design. A Monte Carlo-based approach is employed to quantify how sensor-related uncertainties, such as calibration errors and positioning inaccuracies, affect the spatial distribution of the estimated field's uncertainty. The results offer insights into the robustness of spherical harmonic methods and help identify the dominant sources of uncertainty in practical implementations.