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

[132510]
Title: Magnetic Field Based Similarity Measure for System Matrices in Magnetic Particle Imaging.
Written by: M. Boberg, T. Knopp, and M. Möddel
in: <em>9th International Workshop on Magnetic Particle Imaging (IWMPI 2019)</em>. (2019).
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on pages: 73-74
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Note: inproceedings, multi-patch, magneticfield

Abstract: We introduce a magnetic field based similarity measure for magnetic particle imaging system matrices to ultimately reduce the calibration time for multi-patch reconstructions. The measure gives an idea of how accurate a patch can be reconstructed with a given system matrix. Based on the measure and a chosen number of system matrices one can generate clusters that specify which patch should be reconstructed with which system matrix for optimal results.