The impact of filtering direct-feedthrough on the x-space theory of magnetic particle imaging

Kuan Lu; Patrick Goodwill; Bo Zheng; Steven Conolly

doi:10.1117/12.878446

15 March 2011 The impact of filtering direct-feedthrough on the x-space theory of magnetic particle imaging

Kuan Lu, Patrick Goodwill, Bo Zheng, Steven Conolly

Proceedings Volume 7965, Medical Imaging 2011: Biomedical Applications in Molecular, Structural, and Functional Imaging; 79652I (2011) https://doi.org/10.1117/12.878446
Event: SPIE Medical Imaging, 2011, Lake Buena Vista (Orlando), Florida, United States

Abstract

Magnetic particle imaging (MPI) is a new medical imaging modality that maps the instantaneous response of superparamagnetic particles under an applied magnetic field. In MPI, the excitation and detection of the nanoparticles occur simultaneously. Therefore, when a sinusoidal excitation field is applied to the system, the received signal spectrum contains both harmonics from the particles and a direct feedthrough signal from the source at the fundamental drive frequency. Removal of the induced feedthrough signal from the received signal requires significant filtering, which also removes part of the signal spectrum. In this paper, we present a method to investigate the impact of temporally filtering out individual lower order harmonics on the reconstructed x-space image. Analytic and simulation results show that the loss of particle signal at low frequency leads to a recoverable loss of low spatial frequency information in the x-space image. Initial experiments validate the findings and demonstrate the feasibility of the recovery of the lost signal. This builds on earlier work that discusses the ideal one-dimensional MPI system and harmonic decomposition of the MPI signal.

Citation Download Citation

Kuan Lu, Patrick Goodwill, Bo Zheng, and Steven Conolly "The impact of filtering direct-feedthrough on the x-space theory of magnetic particle imaging", Proc. SPIE 7965, Medical Imaging 2011: Biomedical Applications in Molecular, Structural, and Functional Imaging, 79652I (15 March 2011); https://doi.org/10.1117/12.878446

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