International Journal on Magnetic Particle Imaging (IJMPI)
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Further system characterization of the Single-Sided MPI Scanner with two- and three-dimensional measurements
No full textWith the single-sided MPI-Scanner unlimited object sizes can be measured and it is suitable for various medical applications. In previous measurements, the penetration depth for two-dimensional measurements has already been investigated, as well as the local resolution. The system has evolved from a one-dimensional to a three-dimensional system. Here, further measurements are carried out to characterize the system. To measure the penetration depth and spatial resolution as well as the influence of the orientation of the receiving coils, a four-layer phantom was measured three-dimensionally at different angles. Furthermore, a dilution series was measured to determine the linearity of the system reaction, which is a prerequisite for the quantifiability of the results. The results of both studies are shown and discussed in this work.
Int. J. Mag. Part. Imag. 7(2), 2021, Article ID: 2109001, DOI: 10.18416/IJMPI.2021.210900
Deep image prior for 3D magnetic particle imaging: A quantitative comparison of regularization techniques on Open MPI dataset
No full textMagnetic particle imaging (MPI) is an imaging modality exploiting the nonlinear magnetization behavior of (super-) paramagnetic nanoparticles to obtain a space- and often also time-dependent concentration of a tracer consisting of these nanoparticles. MPI has a continuously increasing number of potential medical applications. One prerequisite for successful performance in these applications is a proper solution to the image reconstruction problem. More classical methods from inverse problems theory, as well as novel approaches from the field of machine learning, have the potential to deliver high-quality reconstructions in MPI. We investigate a novel reconstruction approach based on a deep image prior, which builds on representing the solution by a deep neural network. Novel approaches, as well as variational and iterative regularization techniques, are compared quantitatively in terms of peak signal-to-noise ratios and structural similarity indices on the publicly available Open MPI dataset.
Int. J. Mag. Part. Imag. 7(1), 2021, Article ID: 2103001, DOI: 10.18416/IJMPI.2021.210300
Recent advances and prospects for accelerated development in magnetic particle imaging
No full textThe second issue of the sixth volume of the International Journal on Magnetic Particle Imaging presents three original research papers spanning theoretical and experimental studies designed to improve various aspects of existing MPI technology. The papers present methods for improving image reconstruction processes during magnetic particle imaging by the adoption of new statistical methods, for reducing artifacts in reconstructed images arising from non-ideal selection-field gradients, and a theoretical study modelling how the magnetic particle imaging signal is influenced by parameters of the nanoparticle tracer including the magnetic anisotropy and core radius. The papers provide a snap-shot of current advances in the engineering of magnetic particle imaging systems, and provide insight into how the development and uptake of the technology can be accelerated.
Int. J. Mag. Part. Imag. 6(2), 2021, Article ID: 2106001, DOI: 10.18416/IJMPI.2021.210600
Non-ideal Selection Field Induced Artifacts in X-Space MPI
No full textIn magnetic particle imaging (MPI), the selection field deviates from its ideal linearity in regions away from the center of the scanner. This work demonstrates that unaccounted non-linearity of the selection field causes warping in the image reconstructed with a basic x-space approach. We also show that unwarping algorithms can be applied to effectively address this issue, once the displacement map acting on the reconstructed image is determined. The unwarped image accurately represents the locations of nanoparticles, albeit with a resolution loss in regions away from the center of the scanner due to the degradation in selection field gradients.
Int. J. Mag. Part. Imag. 6(2), 2020, Article ID: 2006001, DOI: 10.18416/IJMPI.2020.200600
Investigating Spatial Resolution, Field Sequences and Image Reconstruction Strategies using Hybrid Phantoms in MPI
No full textHybrid phantoms allow for measurement-based evaluation of particle samples, reconstruction algorithms and field sequences without need of a Magnetic Particle Imaging (MPI) scanning device. Even dynamic hybrid phantoms can be generated using dynamic magnetic offset fields. Multi-dimensional Magnetic Particle Spectrometers are capable of emulating both hybrid system matrices and hybrid phantoms, which can be reconstructed into images. It is shown that a spatial resolution of few hundred micrometres can be achieved for both one- and multi-dimensional excitation using MPI technology. The spatial resolution of reconstructed images increases when including additional receive channels into the reconstruction process. For multi-dimensional imaging the sine-based Lissajous trajectory outperforms the cosine-based Lissajous trajectory in terms of spatial resolution. Both the high signal to noise ratio of a spectrometer and the versatility of hybrid phantom design will enforce innovative measurement-based research on key parameters for MPI.
Int. J. Mag. Part. Imag. 6(1), 2020, Article ID: 2003004, DOI: 10.18416/IJMPI.2020.200300
Super-resolving reconstruction technique for MPI
No full textSystem matrix reconstruction of Magnetic Particle Imaging (MPI) require a time-consuming calibration process. The total number of pixels of the desired image has a direct effect on the calibration time. Although there are various techniques that can shorten the calibration process such as compressive sensing or coded calibration scenes, the increase in total number of pixels still require higher number of samples. In this study, we propose a simple super-resolution technique for MPI images during reconstruction. Using simulations on a field free line MPI scanner system with low drive field amplitude, we show that one can achieve higher resolution images by simply applying super-resolution techniques on the rows of the system matrix. We demonstrate that even simple linear models can help resolve high-resolution structures.
Int. J. Mag. Part. Imag. 6(2), Suppl. 1, 2020, Article ID: 2009071, DOI: 10.18416/IJMPI.2020.200907
Design of a Doubly Tunable Gradiometer Coil
No full textIn a magnetic particle imaging (MPI) scanner, utilizing a tunable gradiometer receive coil can aid in achieving greater degree of decoupling of direct feedthrough signal. However, such a coil can be hard to tune since a very precise positioning of the compensation segment is necessary for excellent decoupling. In this work, we present a doubly tunable gradiometer coil capable of fine tuning without loss of tuning range. We show with experimental results this design can achieve an effective 81.4 dB decoupling in comparison to an identical coil with no gradiometric compensation.
Int. J. Mag. Part. Imag. 6(2), Suppl. 1, 2020, Article ID: 2009064, DOI: 10.18416/IJMPI.2020.200906
Multi-dimensional Harmonic Dispersion X-space MPI
No full textIn magnetic particle imaging (MPI), standard x-space reconstruction requires partial field-of-view (pFOV) processing steps: speed compensation of the received signal and gridding the non-equidistant field free point (FFP) positions to a Cartesian grid. Moreover, due to direct feedthrough filtering, a DC recovery algorithm must be utilized, which requires pFOVs to overlap with each other. In this work, we propose an alternative x-space reconstruction technique that does not require pFOV processing or overlapping pFOVs. The proposed technique is applicable to rapid and sparse multi-dimensional scanning trajectories where standard x-space reconstruction cannot be applied due to non-overlapping pFOVs.
Int. J. Mag. Part. Imag. 6(2), Suppl. 1, 2020, Article ID: 2009062, DOI: 10.18416/IJMPI.2020.200906
Bias-reduction for sparsity promoting regularization in Magnetic Particle Imaging
No full textMagnetic Particle Imaging (MPI) is a tracer based medical imaging modality with great potential due to its high sensitivity, high spatial and temporal resolution, and ability to quantify the tracer concentration. Image reconstruction in MPI is an ill-posed problem that can be addressed by regularization methods that each lead to a bias. Reconstruction bias in MPI is most apparent in a mismatch between true and reconstructed tracer distribution. This is expressed globally in the spatial support of the distribution and locally in its intensity values. In this work, MPI reconstruction bias and its impact are investigated and a two-step debiasing method with significant bias reduction capabilities is introduced.
Int. J. Mag. Part. Imag. 6(2), Suppl. 1, 2020, Article ID: 2009041, DOI: 10.18416/IJMPI.2020.200904
Simulations of magnetic particles with arbitrary anisotropies
No full textTo simulate the behavior of realistic magnetic particles in magnetic particle imaging it is not enough to perform simulations assuming only a uniaxial magnetic anisotropy energy due to the complex coupling between the magnetic and the mechanic degrees of freedom of the particle in multidimensional excitation fields. Most particles can only be approximated of having uniaxial magnetic anisotropy energy. As such, this work will discuss the shortcoming of currently used models focusing on only uniaxial anisotropy and show how a theoretical model must be defined to allow for arbitrary anisotropy energies. First simulation results showing the differences between different anisotropy energies will be presented at the workshop.
Int. J. Mag. Part. Imag. 6(2), Suppl. 1, 2020, Article ID: 2009032, DOI: 10.18416/IJMPI.2020.200903