Literature DB >> 25892744

Flexible and modular MPI simulation framework and its use in modelling a μMPI.

Marcel Straub1, Twan Lammers2, Fabian Kiessling2, Volkmar Schulz3.   

Abstract

The availability of thorough system simulations for detailed and accurate performance prediction and optimization of existing and future designs for a new modality such as magnetic particle imaging (MPI) are very important. Our framework aims to simulate a complete MPI system by providing a description of all (drive and receive) coils, permanent magnet configurations, magnetic nanoparticle (MNP) distributions, and characteristics of the signal processing chain. The simulation is performed on a user defined spatial and temporal discrete grid. The magnetization of the MNP is modelled by either the Langevin theory or as ideal particles with infinite steepness and ideal saturation. The magnetic fields are approximated in first order by calculating the Biot-Savart integral. Additionally the coupling constants between the excitation coils (e.g. drive field coils) and the receive coils can be determined. All coils can be described by an XML description language based on primitive geometric shapes. First simulations of a modelled μMPI system are shown. In this regard μMPI refers to a small one dimensional system for samples of a size of a few tens of a cubic millimeter and a spatial resolution of about 200 μm.

Entities:  

Keywords:  High resolution; MPI; Magnetic Particle Imaging; Simulation

Year:  2015        PMID: 25892744      PMCID: PMC4398983          DOI: 10.1109/TMAG.2014.2329733

Source DB:  PubMed          Journal:  IEEE Trans Magn        ISSN: 0018-9464            Impact factor:   1.700


  8 in total

1.  The signal-to-noise ratio of the nuclear magnetic resonance experiment. 1976.

Authors:  D I Hoult; R E Richards
Journal:  J Magn Reson       Date:  2011-12       Impact factor: 2.229

2.  Tomographic imaging using the nonlinear response of magnetic particles.

Authors:  Bernhard Gleich; Jürgen Weizenecker
Journal:  Nature       Date:  2005-06-30       Impact factor: 49.962

3.  Three-dimensional real-time in vivo magnetic particle imaging.

Authors:  J Weizenecker; B Gleich; J Rahmer; H Dahnke; J Borgert
Journal:  Phys Med Biol       Date:  2009-02-10       Impact factor: 3.609

4.  Quantitative modeling and optimization of magnetic tweezers.

Authors:  Jan Lipfert; Xiaomin Hao; Nynke H Dekker
Journal:  Biophys J       Date:  2009-06-17       Impact factor: 4.033

5.  Analog receive signal processing for magnetic particle imaging.

Authors:  Matthias Graeser; Tobias Knopp; Mandy Grüttner; Timo F Sattel; Thorsten M Buzug
Journal:  Med Phys       Date:  2013-04       Impact factor: 4.071

6.  The X-space formulation of the magnetic particle imaging process: 1-D signal, resolution, bandwidth, SNR, SAR, and magnetostimulation.

Authors:  Patrick W Goodwill; Steven M Conolly
Journal:  IEEE Trans Med Imaging       Date:  2010-06-07       Impact factor: 10.048

7.  A FIELD CANCELATION SIGNAL EXTRACTION METHOD FOR MAGNETIC PARTICLE IMAGING.

Authors:  Volkmar Schulz; Marcel Straub; Max Mahlke; Simon Hubertus; Twan Lammers; Fabian Kiessling
Journal:  IEEE Trans Magn       Date:  2015-02-01       Impact factor: 1.700

8.  Signal encoding in magnetic particle imaging: properties of the system function.

Authors:  Jürgen Rahmer; Jürgen Weizenecker; Bernhard Gleich; Jörn Borgert
Journal:  BMC Med Imaging       Date:  2009-04-01       Impact factor: 1.930

  8 in total
  1 in total

1.  A FIELD CANCELATION SIGNAL EXTRACTION METHOD FOR MAGNETIC PARTICLE IMAGING.

Authors:  Volkmar Schulz; Marcel Straub; Max Mahlke; Simon Hubertus; Twan Lammers; Fabian Kiessling
Journal:  IEEE Trans Magn       Date:  2015-02-01       Impact factor: 1.700

  1 in total

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