Prof. Dr.-Ing. Tobias Knopp

Universitätsklinikum Hamburg-Eppendorf (UKE)
Sektion für Biomedizinische Bildgebung
Lottestraße 55
2ter Stock, Raum 209
22529 Hamburg
Tel.: 040 / 7410 56794
Fax: 040 / 7410 45811
E-Mail: t.knopp(at)uke.de

Technische Universität Hamburg (TUHH)
Institut für Biomedizinische Bildgebung
Gebäude E, Raum 4.044
Am Schwarzenberg-Campus 3
21073 Hamburg
E-Mail: tobias.knopp(at)tuhh.de

 

 

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

[145061]
Title: Suppression of Motion Artifacts Caused by Temporally Recurring Tracer Distributions in Multi-Patch Magnetic Particle Imaging
Written by: N. Gdaniec, M. Boberg, M. Möddel, P. Szwargulski, and T. Knopp
in: IEEE Transactions on Medical Imaging November 2020
Volume: 39 Number: 11
on pages: 3548-3558
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DOI: 10.1109/TMI.2020.2998910
URL: https://ieeexplore.ieee.org/document/9104762
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[doi] [www] [BibTex]

Note: article, multi-patch, artifact, opendata

Abstract: Magnetic particle imaging is a tracer based imaging technique to determine the spatial distribution of superparamagnetic iron oxide nanoparticles with a high spatial and temporal resolution. Due to physiological constraints, the imaging volume is restricted in size and larger volumes are covered by shifting object and imaging volume relative to each other. This results in reduced temporal resolution, which can lead to motion artifacts when imaging dynamic tracer distributions. A common source of such dynamic distributions are cardiac and respiratory motion in in-vivo experiments, which are in good approximation periodic. We present a raw data processing technique that combines data snippets into virtual frames corresponding to a specific state of the dynamic motion. The technique is evaluated on the basis of measurement data obtained from a rotational phantom at two different rotational frequencies. These frequencies are determined from the raw data without reconstruction and without an additional navigator signal. The reconstructed images give reasonable representations of the rotational phantom frozen in several different states of motion while motion artifacts are suppressed.