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

[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.