Néel-rotation physical model for MPI system matrix simulation matches measured 2D data with higher precision than existing models and reduces reconstruction artifacts in phantom experiments.
Numerical Reconstruction in Magnetic Particle Imaging
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abstract
Magnetic particle imaging (MPI) is a medical imaging modality of recent origin, and it exploits the nonlinear magnetization phenomenon to recover the spatially dependent concentration of the nanoparticles. Currently, image reconstruction in MPI is frequently carried out by standard Tikhonov regularization with nonnegativity constraint, which is then minimized by a Kaczmarz type method. In this work, we revisit several issues in the numerical reconstruction in MPI from the perspective of modern inverse theory, i.e., the choice of data fidelity, and choosing a suitable regularization parameter and accelerating Kaczmarz iteration via randomized singular value decomposition. These algorithmic tricks are straightforward to implement and easy to incorporate in existing reconstruction algorithms. Their significant potentials are illustrated by extensive numerical experiments on a publicly available dataset.
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physics.comp-ph 1years
2019 1verdicts
UNVERDICTED 1representative citing papers
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Towards Accurate Modeling of the Multidimensional Magnetic Particle Imaging Physics
Néel-rotation physical model for MPI system matrix simulation matches measured 2D data with higher precision than existing models and reduces reconstruction artifacts in phantom experiments.