Multi-Patch Sequences in Magnetic Particle Imaging

In this project we develop multi-patch imaging sequences and reconstruction algorithms for enlarged measuring fields in magnetic particle imaging (MPI). The regular field-of-view (FOV) in MPI is limited due to physiological constraints such as tissue heating and nerve stimulation. In practice typical FOV are in the range of 2x2x1 cm³. In order to scan larger regions it is possible to shift the FOV to different positions and scan various smaller FOV, which can later be combined to a joint 3D dataset. Especially the reconstruction of multi-patch data is a computationally intensive and memory demanding task. In this project we develop algorithms for efficient reconstruction of multi-patch MPI data.

To reduce calibration time and speed up image reconstruction, we have introduced a number of different methods, including reducing the number of system matricessystem matrix warping, and overscan extrapolation.

Sketch of a multi-patch imaging sequence.

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.