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Advances in Mathematical Physics
Volume 2015, Article ID 472818, 7 pages
http://dx.doi.org/10.1155/2015/472818
Research Article

Local System Matrix Compression for Efficient Reconstruction in Magnetic Particle Imaging

T. Knopp1,2 and A. Weber3

1Section for Biomedical Imaging, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany
2University of Technology, 21073 Hamburg, Germany
3Bruker Biospin MRI, 76275 Ettlingen, Germany

Received 15 October 2014; Revised 11 December 2014; Accepted 11 December 2014

Academic Editor: Xiao-Jun Yang

Copyright © 2015 T. Knopp and A. Weber. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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.