Dr. rer. nat. Martin Möddel (Hofmann)

Universitätsklinikum Hamburg-Eppendorf (UKE)
Sektion für Biomedizinische Bildgebung
Lottestraße 55
2ter Stock, Raum 212
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 56309
E-Mail: m.hofmann(at)uke.de
E-Mail: martin.hofmann(at)tuhh.de
ORCID: https://orcid.org/0000-0002-4737-7863

Research Interests

My research focus is magnetic particle imaging, where I study a number problems such as:

  • Multi-contrast imaging
  • Image reconstruction
  • Signal processing

Curriculum Vitae

Martin Möddel is a postdoc in the group of Tobias Knopp for experimental Biomedical Imaging at the University Medical Center Hamburg-Eppendorf and the Hamburg University of Technology. He received his PhD in physics from the Universität Siegen in 2014 on Characterizing quantum correlations: the genuine multiparticle negativity as entanglement monotone. Prior to his PhD in between 2005-2011 he studied physics at the Universität Leipzig, where he recieved his Diplom On the costratified Hilbert space structure of a lattice gauge model with semi-simple gauge group.

Journal Publications

[164737]
Title: Suppression of Motion Artifacts in Multi-Patch Magnetic Particle Imaging of a Phantom with Periodic Motion.
Written by: M. Boberg, N. Gdaniec, M. Möddel, P. Szwargulski, and T. Knopp
in: <em>SIAM Conference on Imaging Science (IS22)</em>. (2022).
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[BibTex]

Note: inproceedings, multi-patch, artifact

Abstract: Magnetic particle imaging (MPI) is a tracer based imaging technique, which determines the spatial distribution of superparamagnetic iron oxide nanoparticles with a high spatial and temporal resolution. Therefore, MPI is able to image dynamic tracer distributions like cardiac or respiratory motion in in-vivo experiments. As a matter of fact, the imaging volume covers only a few cubic centimeters due to physiological constraints. To cover larger objects a multi-patch approach is used where the imaging volume is shifted relative to the object. Since this reduces the temporal resolution, motion artifacts can occur during the measurement and reconstruction of dynamic tracer distributions. For periodic motions such as the aforementioned cardiac motion, this problem can be solved by reordering the raw measurement data. In a first step, the motion frequency is calculated by analyzing the raw data without reconstruction and without an additional navigator signal. Afterwards data snippets of the raw data corresponding to a specific motion state are rearranged into a virtual frame by using multiple repetitions of the motion state. Finally, the virtual frames can be reconstructed by standard reconstruction techniques. In our experiments, we successfully reconstructed a rotating phantom with a repetition time of 0.56 s without any motion artifacts, while a single full multi-patch measurement cycle takes at least 0.69 s.

[164737]
Title: Suppression of Motion Artifacts in Multi-Patch Magnetic Particle Imaging of a Phantom with Periodic Motion.
Written by: M. Boberg, N. Gdaniec, M. Möddel, P. Szwargulski, and T. Knopp
in: <em>SIAM Conference on Imaging Science (IS22)</em>. (2022).
Volume: Number:
on pages:
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Editor:
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Series:
Address:
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ISBN:
how published:
Organization:
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DOI:
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ARXIVID:
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[BibTex]

Note: inproceedings, multi-patch, artifact

Abstract: Magnetic particle imaging (MPI) is a tracer based imaging technique, which determines the spatial distribution of superparamagnetic iron oxide nanoparticles with a high spatial and temporal resolution. Therefore, MPI is able to image dynamic tracer distributions like cardiac or respiratory motion in in-vivo experiments. As a matter of fact, the imaging volume covers only a few cubic centimeters due to physiological constraints. To cover larger objects a multi-patch approach is used where the imaging volume is shifted relative to the object. Since this reduces the temporal resolution, motion artifacts can occur during the measurement and reconstruction of dynamic tracer distributions. For periodic motions such as the aforementioned cardiac motion, this problem can be solved by reordering the raw measurement data. In a first step, the motion frequency is calculated by analyzing the raw data without reconstruction and without an additional navigator signal. Afterwards data snippets of the raw data corresponding to a specific motion state are rearranged into a virtual frame by using multiple repetitions of the motion state. Finally, the virtual frames can be reconstructed by standard reconstruction techniques. In our experiments, we successfully reconstructed a rotating phantom with a repetition time of 0.56 s without any motion artifacts, while a single full multi-patch measurement cycle takes at least 0.69 s.

Conference Proceedings

[164737]
Title: Suppression of Motion Artifacts in Multi-Patch Magnetic Particle Imaging of a Phantom with Periodic Motion.
Written by: M. Boberg, N. Gdaniec, M. Möddel, P. Szwargulski, and T. Knopp
in: <em>SIAM Conference on Imaging Science (IS22)</em>. (2022).
Volume: Number:
on pages:
Chapter:
Editor:
Publisher:
Series:
Address:
Edition:
ISBN:
how published:
Organization:
School:
Institution:
Type:
DOI:
URL:
ARXIVID:
PMID:

[BibTex]

Note: inproceedings, multi-patch, artifact

Abstract: Magnetic particle imaging (MPI) is a tracer based imaging technique, which determines the spatial distribution of superparamagnetic iron oxide nanoparticles with a high spatial and temporal resolution. Therefore, MPI is able to image dynamic tracer distributions like cardiac or respiratory motion in in-vivo experiments. As a matter of fact, the imaging volume covers only a few cubic centimeters due to physiological constraints. To cover larger objects a multi-patch approach is used where the imaging volume is shifted relative to the object. Since this reduces the temporal resolution, motion artifacts can occur during the measurement and reconstruction of dynamic tracer distributions. For periodic motions such as the aforementioned cardiac motion, this problem can be solved by reordering the raw measurement data. In a first step, the motion frequency is calculated by analyzing the raw data without reconstruction and without an additional navigator signal. Afterwards data snippets of the raw data corresponding to a specific motion state are rearranged into a virtual frame by using multiple repetitions of the motion state. Finally, the virtual frames can be reconstructed by standard reconstruction techniques. In our experiments, we successfully reconstructed a rotating phantom with a repetition time of 0.56 s without any motion artifacts, while a single full multi-patch measurement cycle takes at least 0.69 s.

[164737]
Title: Suppression of Motion Artifacts in Multi-Patch Magnetic Particle Imaging of a Phantom with Periodic Motion.
Written by: M. Boberg, N. Gdaniec, M. Möddel, P. Szwargulski, and T. Knopp
in: <em>SIAM Conference on Imaging Science (IS22)</em>. (2022).
Volume: Number:
on pages:
Chapter:
Editor:
Publisher:
Series:
Address:
Edition:
ISBN:
how published:
Organization:
School:
Institution:
Type:
DOI:
URL:
ARXIVID:
PMID:

[BibTex]

Note: inproceedings, multi-patch, artifact

Abstract: Magnetic particle imaging (MPI) is a tracer based imaging technique, which determines the spatial distribution of superparamagnetic iron oxide nanoparticles with a high spatial and temporal resolution. Therefore, MPI is able to image dynamic tracer distributions like cardiac or respiratory motion in in-vivo experiments. As a matter of fact, the imaging volume covers only a few cubic centimeters due to physiological constraints. To cover larger objects a multi-patch approach is used where the imaging volume is shifted relative to the object. Since this reduces the temporal resolution, motion artifacts can occur during the measurement and reconstruction of dynamic tracer distributions. For periodic motions such as the aforementioned cardiac motion, this problem can be solved by reordering the raw measurement data. In a first step, the motion frequency is calculated by analyzing the raw data without reconstruction and without an additional navigator signal. Afterwards data snippets of the raw data corresponding to a specific motion state are rearranged into a virtual frame by using multiple repetitions of the motion state. Finally, the virtual frames can be reconstructed by standard reconstruction techniques. In our experiments, we successfully reconstructed a rotating phantom with a repetition time of 0.56 s without any motion artifacts, while a single full multi-patch measurement cycle takes at least 0.69 s.