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Local System Matrix Compression for Efficient Reconstruction in Magnetic Particle Imaging

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  • T. Knopp
  • A. Weber

Abstract

Magnetic particle imaging (MPI) is a quantitative method for determining the spatial distribution of magnetic nanoparticles, which can be used as tracers for cardiovascular imaging. For reconstructing a spatial map of the particle distribution, the system matrix describing the magnetic particle imaging equation has to be known. Due to the complex dynamic behavior of the magnetic particles, the system matrix is commonly measured in a calibration procedure. In order to speed up the reconstruction process, recently, a matrix compression technique has been proposed that makes use of a basis transformation in order to compress the MPI system matrix. By thresholding the resulting matrix and storing the remaining entries in compressed row storage format, only a fraction of the data has to be processed when reconstructing the particle distribution. In the present work, it is shown that the image quality of the algorithm can be considerably improved by using a local threshold for each matrix row instead of a global threshold for the entire system matrix.

Suggested Citation

  • T. Knopp & A. Weber, 2015. "Local System Matrix Compression for Efficient Reconstruction in Magnetic Particle Imaging," Advances in Mathematical Physics, John Wiley & Sons, vol. 2015(1).
    • Handle: RePEc:wly:jnlamp:v:2015:y:2015:i:1:n:472818
    DOI: 10.1155/2015/472818
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    References listed on IDEAS

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    1. Bernhard Gleich & Jürgen Weizenecker, 2005. "Tomographic imaging using the nonlinear response of magnetic particles," Nature, Nature, vol. 435(7046), pages 1214-1217, June.
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