A Convex Formulation for Magnetic Particle Imaging X-Space Reconstruction

Justin J Konkle, Patrick W Goodwill, Daniel W Hensley, Ryan D Orendorff, Michael Lustig and Steven M Conolly

PLOS ONE, 2015, vol. 10, issue 10, 1-15

Abstract: Magnetic Particle Imaging (mpi) is an emerging imaging modality with exceptional promise for clinical applications in rapid angiography, cell therapy tracking, cancer imaging, and inflammation imaging. Recent publications have demonstrated quantitative mpi across rat sized fields of view with x-space reconstruction methods. Critical to any medical imaging technology is the reliability and accuracy of image reconstruction. Because the average value of the mpi signal is lost during direct-feedthrough signal filtering, mpi reconstruction algorithms must recover this zero-frequency value. Prior x-space mpi recovery techniques were limited to 1d approaches which could introduce artifacts when reconstructing a 3d image. In this paper, we formulate x-space reconstruction as a 3d convex optimization problem and apply robust a priori knowledge of image smoothness and non-negativity to reduce non-physical banding and haze artifacts. We conclude with a discussion of the powerful extensibility of the presented formulation for future applications.

Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0140137

DOI: 10.1371/journal.pone.0140137

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