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

Journal Publications

[120378]
Title: Determining Perfusion Parameters using Magnetic Particle Imaging: A Phantom Study using a Human-Sized Flow Phantom. <em>9th International Workshop on Magnetic Particle Imaging (IWMPI 2019)</em>
Written by: N. Gdaniec, M. Graeser, F. Thieben, P Szwargulski, F. Werner, M. Boberg, F. Griese, M. Möddel, P. Ludewig, D. van de Ven, O. M. Weber, O. Woywode, B. Gleich, and T. Knopp
in: (2019).
Volume: Number:
on pages: 151-152
Chapter:
Editor:
Publisher:
Series:
Address:
Edition:
ISBN:
how published:
Organization:
School:
Institution:
Type:
DOI:
URL:
ARXIVID:
PMID:

[BibTex]

Note: inproceedings, brainimager

Abstract: The determination of brain perfusion is an important issue for the diagnosis and treatment of vascular diseases. We designed a human-sized dynamic flow phantom mimicking the perfusion properties of the brain and used the human-sized MPI head scanner to acquire data from dynamic bolus injection experiments. A stroke was simulated by occluding one of the feeding hoses. We derived perfusion parameter maps from these data and were able to detect the simulated stroke.

Conference Proceedings

Conference Proceedings

[120378]
Title: Determining Perfusion Parameters using Magnetic Particle Imaging: A Phantom Study using a Human-Sized Flow Phantom. <em>9th International Workshop on Magnetic Particle Imaging (IWMPI 2019)</em>
Written by: N. Gdaniec, M. Graeser, F. Thieben, P Szwargulski, F. Werner, M. Boberg, F. Griese, M. Möddel, P. Ludewig, D. van de Ven, O. M. Weber, O. Woywode, B. Gleich, and T. Knopp
in: (2019).
Volume: Number:
on pages: 151-152
Chapter:
Editor:
Publisher:
Series:
Address:
Edition:
ISBN:
how published:
Organization:
School:
Institution:
Type:
DOI:
URL:
ARXIVID:
PMID:

[BibTex]

Note: inproceedings, brainimager

Abstract: The determination of brain perfusion is an important issue for the diagnosis and treatment of vascular diseases. We designed a human-sized dynamic flow phantom mimicking the perfusion properties of the brain and used the human-sized MPI head scanner to acquire data from dynamic bolus injection experiments. A stroke was simulated by occluding one of the feeding hoses. We derived perfusion parameter maps from these data and were able to detect the simulated stroke.