Artifact Reduction for MPI

High-quality images are essential for any imaging modality to make a reliable diagnosis, and although MPI is highly sensitive, artifacts are common. This issue poses significant challenges for applications that operate in environments with extremely low levels of iron, such as cell tracking. As a result, our objective is to reduce the amount of image artifacts in MPI by implementing different methods in the reconstruction process that allow for these applications. Key components for artifact reduction are:

Extrapolating the system matrix beyond the drive-field field of view reduces artifacts at the patch boundaries in multi-patch imaging scenarios.

Publications

[145061]
Title: Suppression of Motion Artifacts Caused by Temporally Recurring Tracer Distributions in Multi-Patch Magnetic Particle Imaging.
Written by: N. Gdaniec, M. Boberg, M. Möddel, P. Szwargulski, and T. Knopp
in: <em>IEEE Transactions on Medical Imaging</em>. November (2020).
Volume: <strong>39</strong>. Number: (11),
on pages: 3548-3558
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DOI: 10.1109/TMI.2020.2998910
URL: https://arxiv.org/abs/2205.01085
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Note: article, multi-patch, artifact, opendata, openaccess

Abstract: Magnetic particle imaging is a tracer based imaging technique to determine the spatial distribution of superparamagnetic iron oxide nanoparticles with a high spatial and temporal resolution. Due to physiological constraints, the imaging volume is restricted in size and larger volumes are covered by shifting object and imaging volume relative to each other. This results in reduced temporal resolution, which can lead to motion artifacts when imaging dynamic tracer distributions. A common source of such dynamic distributions are cardiac and respiratory motion in in-vivo experiments, which are in good approximation periodic. We present a raw data processing technique that combines data snippets into virtual frames corresponding to a specific state of the dynamic motion. The technique is evaluated on the basis of measurement data obtained from a rotational phantom at two different rotational frequencies. These frequencies are determined from the raw data without reconstruction and without an additional navigator signal. The reconstructed images give reasonable representations of the rotational phantom frozen in several different states of motion while motion artifacts are suppressed.