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

[154730]
Title: Simultaneous imaging of widely differing particle concentrations in MPI: problem statement and algorithmic proposal for improvement.
Written by: M. Boberg, N. Gdaniec, P. Szwargulski, F. Werner, M. Möddel, and T. Knopp
in: <em>Physics in Medicine & Biology</em>. April (2021).
Volume: <strong>66</strong>. Number: (9),
on pages: 095004
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DOI: 10.1088/1361-6560/abf202
URL: https://arxiv.org/abs/2205.01364
ARXIVID:
PMID:

[www] [BibTex]

Note: article, artifact, openaccess

Abstract: Magnetic Particle Imaging (MPI) is a tomographic imaging technique for determining the spatial distribution of superparamagnetic nanoparticles. Current MPI systems are capable of imaging iron masses over a wide dynamic range of more than four orders of magnitude. In theory, this range could be further increased using adaptive amplifiers, which prevent signal clipping. While this applies to a single sample, the dynamic range is severely limited if several samples with different concentrations or strongly inhomogeneous particle distributions are considered. One scenario that occurs quite frequently in pre-clinical applications is that a highly concentrated tracer bolus in the vascular system shadows nearby organs with lower effective tracer concentrations. The root cause of the problem is the ill-posedness of the MPI imaging operator, which requires regularization for stable reconstruction. In this work, we introduce a simple two-step algorithm that increases the dynamic range by a factor of four. Furthermore, the algorithm enables spatially adaptive regularization, i.e. highly concentrated signals can be reconstructed with maximum spatial resolution, while low concentrated signals are strongly regularized to prevent noise amplification.

[154730]
Title: Simultaneous imaging of widely differing particle concentrations in MPI: problem statement and algorithmic proposal for improvement.
Written by: M. Boberg, N. Gdaniec, P. Szwargulski, F. Werner, M. Möddel, and T. Knopp
in: <em>Physics in Medicine & Biology</em>. April (2021).
Volume: <strong>66</strong>. Number: (9),
on pages: 095004
Chapter:
Editor:
Publisher:
Series:
Address:
Edition:
ISBN:
how published:
Organization:
School:
Institution:
Type:
DOI: 10.1088/1361-6560/abf202
URL: https://arxiv.org/abs/2205.01364
ARXIVID:
PMID:

[www] [BibTex]

Note: article, artifact, openaccess

Abstract: Magnetic Particle Imaging (MPI) is a tomographic imaging technique for determining the spatial distribution of superparamagnetic nanoparticles. Current MPI systems are capable of imaging iron masses over a wide dynamic range of more than four orders of magnitude. In theory, this range could be further increased using adaptive amplifiers, which prevent signal clipping. While this applies to a single sample, the dynamic range is severely limited if several samples with different concentrations or strongly inhomogeneous particle distributions are considered. One scenario that occurs quite frequently in pre-clinical applications is that a highly concentrated tracer bolus in the vascular system shadows nearby organs with lower effective tracer concentrations. The root cause of the problem is the ill-posedness of the MPI imaging operator, which requires regularization for stable reconstruction. In this work, we introduce a simple two-step algorithm that increases the dynamic range by a factor of four. Furthermore, the algorithm enables spatially adaptive regularization, i.e. highly concentrated signals can be reconstructed with maximum spatial resolution, while low concentrated signals are strongly regularized to prevent noise amplification.

Conference Proceedings

[154730]
Title: Simultaneous imaging of widely differing particle concentrations in MPI: problem statement and algorithmic proposal for improvement.
Written by: M. Boberg, N. Gdaniec, P. Szwargulski, F. Werner, M. Möddel, and T. Knopp
in: <em>Physics in Medicine & Biology</em>. April (2021).
Volume: <strong>66</strong>. Number: (9),
on pages: 095004
Chapter:
Editor:
Publisher:
Series:
Address:
Edition:
ISBN:
how published:
Organization:
School:
Institution:
Type:
DOI: 10.1088/1361-6560/abf202
URL: https://arxiv.org/abs/2205.01364
ARXIVID:
PMID:

[www] [BibTex]

Note: article, artifact, openaccess

Abstract: Magnetic Particle Imaging (MPI) is a tomographic imaging technique for determining the spatial distribution of superparamagnetic nanoparticles. Current MPI systems are capable of imaging iron masses over a wide dynamic range of more than four orders of magnitude. In theory, this range could be further increased using adaptive amplifiers, which prevent signal clipping. While this applies to a single sample, the dynamic range is severely limited if several samples with different concentrations or strongly inhomogeneous particle distributions are considered. One scenario that occurs quite frequently in pre-clinical applications is that a highly concentrated tracer bolus in the vascular system shadows nearby organs with lower effective tracer concentrations. The root cause of the problem is the ill-posedness of the MPI imaging operator, which requires regularization for stable reconstruction. In this work, we introduce a simple two-step algorithm that increases the dynamic range by a factor of four. Furthermore, the algorithm enables spatially adaptive regularization, i.e. highly concentrated signals can be reconstructed with maximum spatial resolution, while low concentrated signals are strongly regularized to prevent noise amplification.

[154730]
Title: Simultaneous imaging of widely differing particle concentrations in MPI: problem statement and algorithmic proposal for improvement.
Written by: M. Boberg, N. Gdaniec, P. Szwargulski, F. Werner, M. Möddel, and T. Knopp
in: <em>Physics in Medicine & Biology</em>. April (2021).
Volume: <strong>66</strong>. Number: (9),
on pages: 095004
Chapter:
Editor:
Publisher:
Series:
Address:
Edition:
ISBN:
how published:
Organization:
School:
Institution:
Type:
DOI: 10.1088/1361-6560/abf202
URL: https://arxiv.org/abs/2205.01364
ARXIVID:
PMID:

[www] [BibTex]

Note: article, artifact, openaccess

Abstract: Magnetic Particle Imaging (MPI) is a tomographic imaging technique for determining the spatial distribution of superparamagnetic nanoparticles. Current MPI systems are capable of imaging iron masses over a wide dynamic range of more than four orders of magnitude. In theory, this range could be further increased using adaptive amplifiers, which prevent signal clipping. While this applies to a single sample, the dynamic range is severely limited if several samples with different concentrations or strongly inhomogeneous particle distributions are considered. One scenario that occurs quite frequently in pre-clinical applications is that a highly concentrated tracer bolus in the vascular system shadows nearby organs with lower effective tracer concentrations. The root cause of the problem is the ill-posedness of the MPI imaging operator, which requires regularization for stable reconstruction. In this work, we introduce a simple two-step algorithm that increases the dynamic range by a factor of four. Furthermore, the algorithm enables spatially adaptive regularization, i.e. highly concentrated signals can be reconstructed with maximum spatial resolution, while low concentrated signals are strongly regularized to prevent noise amplification.