Low-bandwidth image reconstruction for magnetic particle imaging

Limited Access
This item is unavailable until:
2018-06-09
Date
2017-06
Editor(s)
Advisor
Sarıtaş, Emine Ülkü
Supervisor
Co-Advisor
Co-Supervisor
Instructor
Source Title
Print ISSN
Electronic ISSN
Publisher
Bilkent University
Volume
Issue
Pages
Language
English
Journal Title
Journal ISSN
Volume Title
Series
Abstract

Magnetic Particle Imaging (MPI) is a high contrast tracer imaging modality with applications such as stem cell tracking, angiography and cancer imaging. In MPI, a time-varying magnetic field called the drive field is applied, and the magnetization response of superparamagnetic iron oxide nanoparticles (SPIOs) is recorded. The signal from these nanoparticles is at both drive field frequency and its higher harmonics. However, due to simultaneous excitation and signal reception, the direct feedthrough contaminates the nanoparticle signal at the fundamental harmonic. The direct feedthrough signal can be eliminated using a high-pass filter, where the effect of this filtering has been shown to be a DC loss in image domain. Reliable x-space image reconstruction can then be achieved via enforcing positivity and continuity of the image. However, low SPIO concentrations and/or hardware constraints can further limit the usable signal bandwidth to only a few harmonics. Under low bandwidth signal acquisitions, the loss of higher harmonics results in blurred images after regular x-space reconstruction. This thesis proposes an iterative x-space reconstruction method that recovers not only the lost fundamental harmonic but also the un-acquired higher harmonics for low-bandwidth acquisitions. Proposed method converges to the ideal (i.e., high bandwidth) MPI image in 3-4 iterations. In extensive simulations that incorporate measurement noise and nanoparticle relaxation effects, the proposed method displays improved image quality with respect to the regular x-space reconstruction scheme, with at least 6 dB improvement in peak signal-to-noise ratio (PSNR) metric. Finally, the proposed method is also demonstrated with imaging experiments on an in-house MPI scanner.

Course
Other identifiers
Book Title
Citation
Published Version (Please cite this version)