Prof. Dr.-Ing. Tobias Knopp

Universitätsklinikum Hamburg-Eppendorf (UKE)
Sektion für Biomedizinische Bildgebung
Lottestraße 55
2ter Stock, Raum 209
22529 Hamburg
- Postanschrift -

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

Tel.: 040 / 7410 56794
Fax: 040 / 7410 45811
E-Mail: t.knopp(at)uke.de
E-Mail: tobias.knopp(at)tuhh.de
ORCID: https://orcid.org/0000-0002-1589-8517

 

Roles

  • Head of the Institute for Biomedical Imaging
  • Editor-in-chief of the International Journal on Magnetic Particle Imaging (IJMPI)

Consulting Hours

  • On appointment

Research Interests

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

Curriculum Vitae

Tobias Knopp received his Diplom degree in computer science in 2007 and his PhD in 2010, both from the University of Lübeck with highest distinction. For his PHD on the tomographic imaging method Magnetic Particle Imaging (MPI) he was awarded with the Klee award from the DGBMT (VDE) in 2011. From 2010 until 2011 he led the MAPIT project at the University of Lübeck and published the first scientific book on MPI. In 2011 he joined Bruker Biospin to work on the first commercially available MPI system. From 2012 until 2014 he worked at Thorlabs in the field of Optical Coherence Tomography (OCT) as a software developer. In 2014 he has been appointed as Professor for experimental Biomedical Imaging at the University Medical Center Hamburg-Eppendorf and the Hamburg University of Technology.

Publications

[191970]
Title: Multi-Contrast MPI Matrix Compression.
Written by: L. Nawwas, M. Möddel, and T. Knopp
in: <em>International Journal on Magnetic Particle Imaging</em>. Mar (2025).
Volume: <strong>11</strong>. Number: (1 Suppl 1),
on pages: 1-2
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DOI: https://doi.org/10.18416/IJMPI.2025.2503062
URL: https://www.journal.iwmpi.org/index.php/iwmpi/article/view/888
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Note: inproceedings, artifact

Abstract: Multi-contrast magnetic particle imaging (MPI) reconstructs the signal from different tracer materials or environments, resulting in multi-channel images that enable temperature or viscosity quantification. Since the multi-contrast problem is ill-posed, it is addressed by regularization methods that are commonly solved using the Kaczmarz algorithm. Unlike the single-contrast MPI problem, the multi-contrast one requires a high number of iterations to converge. Matrix compression techniques were already successfully used in single-contrast reconstruction and matrix recovery applications as in compressed sensing. Our work proposes to use matrix compression to reduce the reconstruction time needed to achieve good reconstruction quality in multi-contrast MPI.