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

[180972]
Title: Boundary artifact reduction by extrapolating system matrices outside the field-of-view in joint multi-patch MPI.
Written by: K. Scheffler, M. Boberg, and T. Knopp
in: <em>International Journal on Magnetic Particle Imaging</em>. (2022).
Volume: <strong>8</strong>. Number: (1),
on pages: 1-3
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DOI: 10.18416/IJMPI.2022.2203019
URL: https://journal.iwmpi.org/index.php/iwmpi/article/view/348
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Note: inproceedings, artifact, multi-patch

Abstract: In multi-patch magnetic particle imaging an artifact-free image can be obtained by using a joint reconstruction and measuring the system matrices not only in the field-of-view but also in a huge overscan. This leads to a long calibration time and heavy memory consumption and therefore an unsuitability of this method for large three-dimensional measurements. In this work we propose to measure the system matrices only in the field-of-view and use a diffusion based extrapolation step to extant the system matrices computationally into the overscan. In this way we massively reduce the calibration time while maintaining a nearly artifact-free image.