Dr.-Ing. Matthias Gräser

Universitätsklinikum Hamburg-Eppendorf (UKE)
Sektion für Biomedizinische Bildgebung
Lottestraße 55
2ter Stock, Raum 212
22529 Hamburg

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

Tel.: 040 / 7410 25812
E-Mail: matthias.graeser(at)tuhh.de
E-Mail: ma.graeser(at)uke.de

Research Interests

  • Magnetic Particle Imaging
  • Low Noise Electronics
  • Inductive Sensors
  • Passive Electrical Devices

Curriculum Vitae

Matthias Gräser submitted his Dr.-Ing. thesis in january 2016 at the institute of medical engineering (IMT) at the university of Lübeck and is now working as a Research Scientist at the institute for biomedical imaging (IBI) at the technical university in Hamburg, Germany.  Here he develops concepts for Magnetic-Particle-Imaging (MPI) devices. His main aim is to improve the sensitivity of the imageing devices and improve resolution and application possibilities of MPI technology.

In 2011 Matthias Gräser started to work at the IMT as a Research Associate in the Magnetic Particle Imaging Technology (MAPIT) project. In this project he devolped the analog signal chains for a rabbit sized field free line imager. Additionally he developed a two-dimensional Magnetic-Particle-Spectrometer. This device can apply various field sequences and measure the particle response with a very high signal-to-noise ratio (SNR).

The dynamic behaviour of magnetic nanoparticles is still not fully understood. Matthias Gräser investigated the particle behaviour by modeling the particle behaviour with stochastic differential equations. With this model it is possible to simulate the impact of several particle parameters and field sequences on the particle response .

In 2010 Matthias Gräser finished his diploma at the Karlsruhe Institue of Technology (KIT). His diploma thesis investigated the nerve stimulation of magnetic fields in the range from 4 kHz to 25 kHz.

Journal Publications

[76880]
Title: Electronic field free line rotation and relaxation deconvolution in {Magnetic Particle Imaging}.
Written by: K. Bente, M. Weber, M. Graeser, T.F. Sattel, M. Erbe, and T.M. Buzug
in: <em>{{IEEE} Transactions on Medical Imaging},</em>. (2015).
Volume: <strong>34</strong>. Number: (2),
on pages: 644--651
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DOI: 10.1109/TMI.2014.2364891
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[BibTex]

Note: article

Abstract: It has been shown that magnetic particle imaging ({MPI}), an imaging method suggested in 2005, is capable of measuring the spatial distribution of magnetic nanoparticles. Since the particles can be administered as biocompatible suspensions, this method promises to perform well as a tracer-based medical imaging technique. It is capable of generating real-time images, which will be useful in interventional procedures, without utilizing any harmful radiation. To obtain a signal from the administered superparamagnetic iron oxide ({SPIO}) particles, a sinusoidal changing external homogeneous magnetic field is applied. To achieve spatial encoding, a gradient field is superimposed. Conventional {MPI} works with a spatial encoding field that features a field free point ({FFP}). To increase sensitivity, an improved spatial encoding field, featuring a field free line ({FFL}) can be used. Previous {FFL} scanners, featuring a 1-D excitation, could demonstrate the feasibility of the {FFL}-based {MPI} imaging process. In this work, an {FFL}-based {MPI} scanner is presented that features a 2-D excitation field and, for the first time, an electronic rotation of the spatial encoding field. Furthermore, the role of relaxation effects in {MPI} is starting to move to the center of interest. Nevertheless, no reconstruction schemes presented thus far include a dynamical particle model for image reconstruction. A first application of a model that accounts for relaxation effects in the reconstruction of {MPI} images is presented here in the form of a simplified, but well performing strategy for signal deconvolution. The results demonstrate the high impact of relaxation deconvolution on the {MPI} imaging process.

Conference Proceedings

[76880]
Title: Electronic field free line rotation and relaxation deconvolution in {Magnetic Particle Imaging}.
Written by: K. Bente, M. Weber, M. Graeser, T.F. Sattel, M. Erbe, and T.M. Buzug
in: <em>{{IEEE} Transactions on Medical Imaging},</em>. (2015).
Volume: <strong>34</strong>. Number: (2),
on pages: 644--651
Chapter:
Editor:
Publisher:
Series:
Address:
Edition:
ISBN:
how published:
Organization:
School:
Institution:
Type:
DOI: 10.1109/TMI.2014.2364891
URL:
ARXIVID:
PMID:

[BibTex]

Note: article

Abstract: It has been shown that magnetic particle imaging ({MPI}), an imaging method suggested in 2005, is capable of measuring the spatial distribution of magnetic nanoparticles. Since the particles can be administered as biocompatible suspensions, this method promises to perform well as a tracer-based medical imaging technique. It is capable of generating real-time images, which will be useful in interventional procedures, without utilizing any harmful radiation. To obtain a signal from the administered superparamagnetic iron oxide ({SPIO}) particles, a sinusoidal changing external homogeneous magnetic field is applied. To achieve spatial encoding, a gradient field is superimposed. Conventional {MPI} works with a spatial encoding field that features a field free point ({FFP}). To increase sensitivity, an improved spatial encoding field, featuring a field free line ({FFL}) can be used. Previous {FFL} scanners, featuring a 1-D excitation, could demonstrate the feasibility of the {FFL}-based {MPI} imaging process. In this work, an {FFL}-based {MPI} scanner is presented that features a 2-D excitation field and, for the first time, an electronic rotation of the spatial encoding field. Furthermore, the role of relaxation effects in {MPI} is starting to move to the center of interest. Nevertheless, no reconstruction schemes presented thus far include a dynamical particle model for image reconstruction. A first application of a model that accounts for relaxation effects in the reconstruction of {MPI} images is presented here in the form of a simplified, but well performing strategy for signal deconvolution. The results demonstrate the high impact of relaxation deconvolution on the {MPI} imaging process.