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

[120343]
Title: Magnetic field based system matrix corrections for multi-patch MPI reconstructions.
Written by: M. Boberg, M. Möddel, and T. Knopp
in: <em>9th International Congress on Industrial and Applied Mathematics (ICIAM 2019)</em>. (2019).
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on pages: 333
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URL: https://iciam2019.org/images/site/news/ICIAM2019_PROGRAM_ABSTRACTS_BOOK.pdf#page=333
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Note: inproceedings, multi-patch, artifact

Abstract: Magnetic particle imaging is an imaging modality, which determines the spatial distribution of super-paramagnetic nanoparticles by solving a linear system of equations. Using multi-patch approaches the field-of-view in MPI can be enlarged. Due to field imperfections a dedicated system matrix for each patch is required to reduce artifacts in the reconstructed image. However, this results in long calibration times. In this talk, techniques are presented to reduce the calibration time while maintaining high quality.