International Journal on Magnetic Particle Imaging (IJMPI)
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L1 data fitting for robust reconstruction in magnetic particle imaging: quantitative evaluation on Open MPI dataset
No full textMagnetic particle imaging is an emerging quantitative imaging modality, exploiting the unique nonlinear magnetization phenomenon of superparamagnetic iron oxide nanoparticles for recovering the concentration. Traditionally the reconstruction is formulated into a penalized least-squares problem with nonnegativity constraint, and then solved using a variant of Kaczmarz method which is often stopped early after a small number of iterations. Besides the phantom signal, measurements additionally include a background signal and a noise signal. In order to obtain good reconstructions, a preprocessing step of frequency selection to remove the deleterious influences of the noise is often adopted. In this work, we propose a complementary pure variational approach to noise treatment, by viewing highly noisy measurements as outliers, and employing the l1 data fitting, one popular approach from robust statistics. When compared with the standard approach, it is easy to implement with a comparable computational complexity. Experiments with a public domain dataset, i.e., Open MPI dataset, show that it can give accurate reconstructions, and is less prone to noisy measurements, which is illustrated by quantitative (PSNR / SSIM) and qualitative comparisons with the Kaczmarz method. We also investigate the performance of the Kaczmarz method for small iteration numbers quantitatively.
Int. J. Mag. Part. Imag. 6(2), 2020, Article ID: 2012001, DOI: 10.18416/IJMPI.2020.201200
Eigen-reconstructions: a closer look into the System Matrix
No full textMagnetic particle imaging (MPI) offers an exceptional set of advantages including high sampling efficiency and sub-millimeter spatial resolution. The former is maximized using ad-hoc sampling trajectories; the latter relies on the compensation of the point spread function of the superparamagnetic iron oxide particles (SPIOs) necessary for the MPI signal. The System Matrix (SM) approach for reconstruction uses a pre-calibration measurement and achieves both purposes simultaneously, relating the concentration of SPIOs and the particle response to the signal. Consequently, the SM’s quality will largely influence the reconstruction. Considering the multitude of factors involved in the reconstruction, it is difficult to identify sources of image artifacts. In this work, we demonstrate the potential to use reconstructions of individual measurements within the SM (eigen-reconstruction) as a test for both SM and reconstruction quality. We also present an algorithm to enhance image quality using eigen-reconstructions.
Int. J. Mag. Part. Imag. 6(2), Suppl. 1, 2020, Article ID: 2009072, DOI: 10.18416/IJMPI.2020.200907
A novel representation of the MPI system function
No full textIn a recent publication, based on the Langevin model, the exact mathematical relationship between the system function and tensor products of Chebyshev polynomials of second kind has been derived for the case in which multidimensional excitation is used for magnetic particle imaging. There, a new expression for the system function in magnetic particle imaging was derived. To make this representation easily accessible, the present paper focusses on the more practical aspects of the theory without going deep into the mathematical proofs. In particular, we examine the contribution of the mixing factors to the total energy of a system function component.
Int. J. Mag. Part. Imag. 6(2), Suppl. 1, 2020, Article ID: 2009050, DOI: 10.18416/IJMPI.2020.200905
Iron core coil designs for MPI
No full textIn Magnetic Particle Imaging, much of the power consumed during an imaging sequence is used for the generation of the selection and focus fields. In today’s MPI scanners three different concepts are applied to generate the gradient fields: Air coils, permanent magnets and coils with soft iron. Air coils and permanent magnets have the great advantage of good calculability by the Biot-Savart Law. On the way to a clinical imaging modality, the needed power for sufficient gradient strength demand the use of soft iron. In order to make good use of the ferromagnetic amplification properties, much more complex simulations have to be done. A recently published head scanner uses a soft iron yoke for field generation. In this study, we investigated different coil geometries with soft iron with respect to this head scanner.
Int. J. Mag. Part. Imag. 6(2), Suppl. 1, 2020, Article ID: 2009042, DOI: 10.18416/IJMPI.2020.200904
Enhanced compressed sensing recovery of multi-patch system matrices in MPI
No full textIn magnetic particle imaging, the time consuming measurement of a system matrix is required before image reconstruction.Reduction of measurement time can be achieved with the help of compressed sensing, which is based on the sparsity of the systemmatrix in a suitable transform domain. In this work, we propose regularization functions to exploit the additional correlations in multi-patch system matrices. Experiments show that the resulting recovery method allows successful matrix recovery at higherundersampling factors than a standard compressed sensing recovery.
Int. J. Mag. Part. Imag. 6(2), Suppl. 1, 2020, Article ID: 2009035, DOI: 10.18416/IJMPI.2020.200903
First images obtained with a rabbit-sized Magnetic Particle Imaging scanner
No full textThe subject of this work is a magnetic-particle-imaging system featuring a field generator with an inner bore diameter of 180 mm. The scanner, which is large enough to accommodate small animals, is capable of generating a selection field either with a field free point or with a field free line. In this work, the imaging system is used to acquire two-dimensional data from a particle distribution using a field free point to record a system matrix. Finally, a plain particle phantom is measured to evaluate the imaging data and show the first two-dimensional image that is recorded with this setup.
Int. J. Mag. Part. Imag. 6(2), Suppl. 1, 2020, Article ID: 2009033, DOI: 10.18416/IJMPI.2020.200903
Estimating orientation using multi-contrast MPI
No full textMagnetic particle imaging (MPI) is a tracer based tomographic imaging technique that uses static and oscillating magnetic fields to generate an image contrast from the spatial distribution of magnetic nanoparticles. Recent investigations have shown that the MPI is able to generate additional contrasts from different tracer materials or their environments. For example, multi-contrast MPI can be used to determine the viscosity or temperature of the particle environment, or to distinguish tracer particles based on their core size. In this work, we investigate a novel contrast based on the magnetic anisotropy of immobilized particles which allows to estimate the orientation of samples.
Int. J. Mag. Part. Imag. 6(2), Suppl. 1, 2020, Article ID: 2009023, DOI: 10.18416/IJMPI.2020.200902
Spatial selectivity enhancement in RF-hyperthermia by magnetic flux confinement
No full textAiming to increase spatial selectivity which provides the precision in hyperthermia therapy and high resolution in imaging, we propose a strategy to increase field gradient for Magnetic Particle Imaging (MPI) modality. In this study, a solution for an existing MPI system topology was simulated, which uses additional soft magnetic material as iron core retrofit at the center of selection field coil. Due to core property of high magnetic permeability relative to air, magnetic flux gets confined to increase selection field gradient field slope. Within this simulation study, the optimal core position is evaluated whilst its effects on the magnet system is validated. We found that this technique increases the magnetic field gradient up to a factor of 1.4 from 2.5 T/m to 3.4 T/m in z-direction, without significant loading of the drive field resonance circuit due to power losses caused by eddy currents in the MPI compatible iron core shielding.
Int. J. Mag. Part. Imag. 6(2), Suppl. 1, 2020, Article ID: 2009015, DOI: 10.18416/IJMPI.2020.200901
Functional MPI (fMPI) of hypercapnia in rodent brain with MPI time-series imaging
No full textMPI has been proposed as an alternative to fMRI for detecting cerebral blood volume (CBV) changes associated with brain activation due to potentially higher sensitivity, possibly enabling single-patient studies. In this work, we show preliminary neuroimaging data of CBV modulation with hypercapnia acquired in vivo on a rodent MPI scanner designed for time-series imaging. This continuously rotating 2D projection field free line imager enables time-series imaging with temporal resolution of up to 3 seconds. As a first demonstration of “fMPI”, we acquire time-series images of a rodent brain with 5 second temporal resolution with the animal undergoing alternating 3-minute periods of either hyper- or hypocapnia. Image intensity changes from CBV modulation of the injected SPIONs concentration were detected with a CNR of up to 14 in brain pixels.
Int. J. Mag. Part. Imag. 6(2), Suppl. 1, 2020, Article ID: 2009009, DOI: 10.18416/IJMPI.2020.200900
Design of A Rabbit Scale 3D Magnetic Particle Imaging System with Amplitude Modulation
No full textMagnetic Particle Imaging (MPI) is a fast and sensitive imaging method that can be used to measure the spatial distribution of superparamagnetic iron oxide (SPIO) nanoparticles. To overcome some limitations of general MPI, the Amplitude Modulation MPI (AM MPI), which uses a low-amplitude excitation field combined with a low-frequency drive field, was suggested. In this paper, we present the design of a rabbit scale 3D AM MPI system with a larger bore size (9 cm). The AM MPI can reach a drive-field field-of-view (DF-FOV) of 4.00 x 4.00 x 8.00 cm and a whole field-of-view (W-FOV) of 6.36 x 6.36 x 8.00 cm at 2.2 T/m.
Int. J. Mag. Part. Imag. 6(2), Suppl. 1, 2020, Article ID: 2009067, DOI: 10.18416/IJMPI.2020.200906