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: martin.moeddel(at)tuhh.de
E-Mail: m.hofmann(at)uke.de
ORCID: https://orcid.org/0000-0002-4737-7863

Research Interests

My research on tomographic imaging is primarily focused on magnetic particle imaging. In this context, I am engaged in the study of a number of problems, including:

  • Image reconstruction
    • Multi-contrast imaging
    • Multi-patch imaging
    • Artifact reduction
  • Magnetic field generation and characterisation
  • Receive path calibration

Curriculum Vitae

Martin Möddel is a postdoctoral researcher 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 the topic of characterizing quantum correlations: the genuine multiparticle negativity as entanglement monotone. Prior to his PhD, he studied physics at the Universität Leipzig between 2005 and 2011, where he received his Diplom On the costratified Hilbert space structure of a lattice gauge model with semi-simple gauge group.

Journal 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: <em>IEEE Transactions on Medical Imaging</em>. November (2020).
Volume: <strong>39</strong>. Number: (11),
on pages: 3548-3558
Chapter:
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how published:
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DOI: 10.1109/TMI.2020.2998910
URL: https://arxiv.org/abs/2205.01085
ARXIVID:
PMID:

[www] [BibTex]

Note: article, multi-patch, artifact, opendata, openaccess

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.

[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: <em>IEEE Transactions on Medical Imaging</em>. November (2020).
Volume: <strong>39</strong>. Number: (11),
on pages: 3548-3558
Chapter:
Editor:
Publisher:
Series:
Address:
Edition:
ISBN:
how published:
Organization:
School:
Institution:
Type:
DOI: 10.1109/TMI.2020.2998910
URL: https://arxiv.org/abs/2205.01085
ARXIVID:
PMID:

[www] [BibTex]

Note: article, multi-patch, artifact, opendata, openaccess

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.

Conference Proceedings

[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: <em>IEEE Transactions on Medical Imaging</em>. November (2020).
Volume: <strong>39</strong>. Number: (11),
on pages: 3548-3558
Chapter:
Editor:
Publisher:
Series:
Address:
Edition:
ISBN:
how published:
Organization:
School:
Institution:
Type:
DOI: 10.1109/TMI.2020.2998910
URL: https://arxiv.org/abs/2205.01085
ARXIVID:
PMID:

[www] [BibTex]

Note: article, multi-patch, artifact, opendata, openaccess

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.

[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: <em>IEEE Transactions on Medical Imaging</em>. November (2020).
Volume: <strong>39</strong>. Number: (11),
on pages: 3548-3558
Chapter:
Editor:
Publisher:
Series:
Address:
Edition:
ISBN:
how published:
Organization:
School:
Institution:
Type:
DOI: 10.1109/TMI.2020.2998910
URL: https://arxiv.org/abs/2205.01085
ARXIVID:
PMID:

[www] [BibTex]

Note: article, multi-patch, artifact, opendata, openaccess

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.