Fast Trajectory-Independent Model-Based Reconstruction Algorithm for Multi-Dimensional Magnetic Particle Imaging

• URL: http://arxiv.org/abs/2505.22797v1
• Date: Wed, 28 May 2025 19:13:46 GMT
• Title: Fast Trajectory-Independent Model-Based Reconstruction Algorithm for Multi-Dimensional Magnetic Particle Imaging
• Authors: Vladyslav Gapyak, Thomas März, Andreas Weinmann,
• Abstract summary: 2D Particleoidal Imaging (MPI) is a promising technique for visualizing the distribution of superparamagnetic nanoparticles.<n>MPI reconstruction relies on either time-consuming distribution system matrix or model-based simulation of the forward operator.<n>In this paper we present the first reconstruction on real trajectory-independent MPI data with a model-based MPI reconstruction.
• Score: 1.7614751781649953
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Magnetic Particle Imaging (MPI) is a promising tomographic technique for visualizing the spatio-temporal distribution of superparamagnetic nanoparticles, with applications ranging from cancer detection to real-time cardiovascular monitoring. Traditional MPI reconstruction relies on either time-consuming calibration (measured system matrix) or model-based simulation of the forward operator. Recent developments have shown the applicability of Chebyshev polynomials to multi-dimensional Lissajous Field-Free Point (FFP) scans. This method is bound to the particular choice of sinusoidal scanning trajectories. In this paper, we present the first reconstruction on real 2D MPI data with a trajectory-independent model-based MPI reconstruction algorithm. We further develop the zero-shot Plug-and-Play (PnP) algorithm of the authors -- with automatic noise level estimation -- to address the present deconvolution problem, leveraging a state-of-the-art denoiser trained on natural images without retraining on MPI-specific data. We evaluate our method on the publicly available 2D FFP MPI dataset ``MPIdata: Equilibrium Model with Anisotropy", featuring scans of six phantoms acquired using a Bruker preclinical scanner. Moreover, we show reconstruction performed on custom data on a 2D scanner with additional high-frequency excitation field and partial data. Our results demonstrate strong reconstruction capabilities across different scanning scenarios -- setting a precedent for general-purpose, flexible model-based MPI reconstruction.

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