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

[164736]
Title: Fast and artifact reducing joint multi-patch MPI reconstruction.
Written by: L. Zdun, M. Boberg, and C. Brandt
in: <em>International Journal on Magnetic Particle Imaging</em>. (2022).
Volume: <strong>8</strong>. Number: (1),
on pages: 1-4
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DOI: 10.18416/IJMPI.2022.2203042
URL: https://journal.iwmpi.org/index.php/iwmpi/article/view/437
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Note: inproceedings, multi-patch, artifact

Abstract: The method of magnetic particle imaging has a limited field of view due to physiological constraints. It is thus necessary to enlarge the field of view by a multi-patch approach in order to cover larger volumes. During reconstruction, truncation artifacts arise at the patches boundaries. We apply stochastic primal-dual hybrid gradient method to jointly reconstruct multi-patch magnetic particle images. We are thus able to apply a regularization, which takes into account neighborhood structures, not only on one patch but over all patches. Our experiments show that the quality of our reconstructions is significantly higher than the ones of reconstructions obtained by Kaczmarz method. Moreover, a joint reconstruction can considerably reduce the computational costs compared to multiple single-patch reconstructions.