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Joint Reconstruction of Tracer Distribution and Background in Magnetic Particle Imaging


3D Reconstruction in Canonical

Class Agnostic Image Common Ob
Abstract


Magnetic particle imaging (MPI) is a novel tomographic imaging technique which visualizes the distribution of a magnetic nanoparticle based tracer material. However, reconstructed MPI images often suffer from an insufficiently compensated image background caused by rapid non-deterministic changes in the background signal of the imaging device. In particular, the signal to background ratio (SBR) of the images is reduced for lower tracer concentrations or longer acquisitions. The state of the art procedure in MPI is to frequently measure the background signal during the sample measurement. Unfortunately, this requires a removal of the entire object from the scannerÔ??s field of view (FOV) which introduces dead time and repositioning artifacts. To overcome these considerable restrictions, we propose a novel method that uses two consecutive image acquisitions as input parameters for a simultaneous reconstruction of the tracer distribution as well as the background signal. The two acquisitions differ by just a small spatial shift, while keeping the object always within the focus of a slightly reduced FOV. A linearly interpolated background between the initial and final background measurement is used to seed the iterative reconstruction. The method has been tested with simulations and phantom measurements. Overall, a substantial reduction of the image background was observed and the image SBR is increased by a factor of 2(7) for the measurement (simulation) data

KeyWords
magnetic particle imaging (MPI), background signal, reconstruction, artifact suppression, least squares



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