International Journal on Magnetic Particle Imaging (IJMPI)
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A Zero-Shot L1-Plug-and-Play Approach for System-Matrix-Based MPI
No full textThe MPI reconstruction task in the system-matrix-based approach is an example of a severely ill-posed inverse problem that requires regularization. Part of the ill-posedness arises from the noise present in the MPI measurements and in the calibration data. For this reason, various pre-processing steps are applied to mitigate the effect of the noise, among which are bandpass filtering, whitening and lower rank approximation via randomized SVD of the system matrix. Recently, Plug-and-Play (PnP) approaches for inverse problems have been developed. These approaches are iterative reconstruction schemes that iteratively alternate between a reconstruction step and a Gaussian denoising step. Previous PnP approaches applied to MPI employ a denoiser which has been trained on MPI-friendly data. In this work we propose an L1-PnP approach that employs a zero-shot denoiser (trained on natural images and without further fine-tuning). We validate the approach on the 3D OpenMPI Dataset. Moreover, we compare the approach with reconstructions obtained with the standard Tikhonov reconstruction method and the Deep Image Prior, and show reconstructions with increasingly lower levels of pre-processing of the data, suggesting insensitivity of the L1-PnP method to different pre-processing steps
Deep Learning Inpainting Approach for FFL-MPI sinograms
No full textIn Magnetic Particle Imaging (MPI), field-free line (FFL) encoding allows for setting up sinograms and use well-known algorithms from Computed Tomography (CT) for image reconstruction. Here, an FFL trajectory with a drive field (DF) direction orthogonal to rotation and translation direction of the FFL is considered. The reconstruction of each DF cycle is mapped to several sinograms along DF direction, which may result in holes within the sinograms.
To fill these holes, a CT inpainting approach based on Deep Learning algorithms is adapted. Therefore, different neural network architectures were used. A U-Network, showing good results for inpainting tasks and a generative adversarial network to use a second network for evaluation of image quality. Experiments with different learning rates, architectures, encoders, data augmentation, partial convolution layers and dual domain loss have been performed and evaluated.
For training, two data sets were created. From CT data intrathoracic and lower limb vessel structures were segmented to mimic MPI images. Dataset1 presents ideal information, i.e. images were transformed to radon space resulting in ideal sinograms. Dataset2 consists of synthesized MPI measurement data. Each data sets includes 12080 sinograms, split in train (60%), validation (20%) and test (20%) data.
Training was started with Dataset1 and one configuration including holes. The optimum was a U-Network with a learning rate of 10-4, early stopping, ResNet50 encoder and partial convolution layers. The pre-trained network was further trained with Dataset2. This improved the performance for actual MPI measurement data. The optimized network was successfully applied for different hole configurations
Analysis of noise sources in a human-scale fMPI imager
No full textHigh sensitivity is a key benefit of magnetic particle imaging (MPI) and drives many of its application, including functional neuroimaging (fMPI). Since the thermal noise levels expected from the preamplifier and coil resistance are quite low, it is crucial to identify, characterize and remove any sources of "noise" generated from system instabilities. These include fluctuations in the gain or production of genuine harmonics originating from the SPIONs as well as nuisance fluctuations of empty-bore signals at each harmonic frequency. While stable empty-bore harmonic signals can be calibrated and subtracted from the detected data, uncontrolled variance in their levels appears as "noise" and can ultimately limit the achievable signal-to-noise ratio (SNR) of the scanner. Here, we present a characterization of these noise source mechanisms in our human-scale field-free line (FFL) fMPI scanner. Currently, the shift amplifier, which is responsible for the translation of the FFL across the field of view (FOV), is the dominant source of noise. Eliminating the shift noise and improving the system’s stability would improve our sensitivity from our current detection limit of 150 ng to 15 ng of iron, a 10× improvement
A Deep Equilibrium Technique for 3D MPI Reconstruction
No full textImage reconstruction in MPI involves estimation of the particle concentration given acquired data and system matrix (SM). As this is an ill-posed inverse problem, image quality depends heavily on prior information used to improve problem conditioning. Recent learning-based priors show great promise for MPI reconstruction, but priors purely driven by image samples in training datasets can show limited reliability and generalization. Here, we propose 3DEQ-MPI, a new deep equilibrium technique for 3D MPI reconstruction. 3DEQ-MPI is based on an infinitely-unrolled network architecture that synergistically leverages a data-driven prior to learn attributes of MPI images and a physics-driven prior to enforce fidelity to acquired data based on the SM. 3DEQ-MPI is trained on a simulated dataset, and unlike common deep equilibrium models, it utilizes a Jacobian-free backpropagation algorithm for fast and stable convergence. Demonstrations on simulated data and experimental OpenMPI data clearly show the superior performance of 3DEQ-MPI against competing methods
Analysis of nucleation and Growth using INSPECT II for co-precipitation methodology-based synthesis
No full textMagnetic particle imaging (MPI) is a quantitative imaging modality which provides information on the spatial distribution of magnetic nanoparticles (MNPs). Magnetic particle spectrometry (MPS) is a characterization tool which helps in determining the magnetic properties of these synthesized MNPs. As MNPs directly influence the image resolution, therefore different approaches are used to improve the magnetic properties of these MNPs both chemically and by changing the synthesis environment. Last year, INSPECT II with a fully controllable temperature bath for maximizing control of the synthesis environment and simultaneously determining the magnetic properties of MNPs during the synthesis process was introduced. INSPECT II is tuned to the sinusoidal excitation frequency of 25 kHz at 10 mT. In this setup a volume of 50 ml of a suspension of MNPs can easily be synthesized. A chemical reaction based on the co-precipitation methodology was carried out inside INSPECT II to analyze the nucleation and growth of the synthesized magnetic nanoparticles (MNPs). In this research, the change in magnetic properties of SPIONs was tracked with the help of INSPECT II during one complete synthesis. The synthesis lasted for 140 minutes and consisted of 70 measurements. INSPECT II was able to observe and record the change in magnetic properties of the synthesized nanoparticles and the obtained results in terms of change in magnetic moment versus time will be presented. The synthesis process used for the validation of INSPECT II is the co-precipitation synthesis based on the methods developed by Lüdtke-Buzug et al
Development of magnetic particle imaging modules using high-Tc superconducting coils
No full textMagnetic particle imaging (MPI), in which harmonic magnetization signals from magnetic nanoparticles are detected to image diseased regions with high sensitivity, is attracting attention. In MPI, the spatial resolution of the image is mainly determined by the DC magnetic field gradient of the scanner, and MPI scanners only for small animal size were commercialized at the present stage. In this work, we developed magnetic particle imaging modules with 120 mm bore diameter using yttrium barium copper oxide (YBCO) high temperature superconducting (HTS) tape as a selection field coil. The gradient field of 0.63 T/m is realized with the developed YBCO HTS coil cooled with liquid nitrogen (LN). The power consumption and the mass of the HTS selection field coil could be reduced compared with a Cu coil and it indicates that utilizing a HTS selection field coil is one of the best options toward the realization of human-body-sized MPI scanner
Magneto-mechanical stimulation of living cells: towards innovative therapies based on mechanobiological effects
No full textCellular mechano-sensitivity can be exploited to modify cellular functions, opening the doors to the design of innovative therapies. This can be very efficiently achieved through the use of magnetic microparticles dispersed among the cells and actuated in a remotely controlled manner by external variable magnetic fields. Experiments were conducted on glioma cancer cell lines under several conditions: in-vitro 2D in Petri dishes, in-vitro 2D on soft substrates, in-vitro 3D on organoïds/tumoroïds and in-vivo on mice. The possibility to destroy cancer cells in-vitro by magneto-mechanical stimulation was clearly demonstrated. The comparison between the different experimental conditions revealed the key role of the microenvironment on cells physiological reactions to the magneto-mechanical stimulation. It appears that the organoïds/tumoroïds provide a very relevant in-vitro model for the study of these mechanobiological effects before translation to in-vivo studies
Development of human head size Magnetic Particle Imaging system
No full textThe magnetic particle imaging device deploys an alternating magnetic field generated by a coil to induce magnetic signals from magnetic particles injected into the body; it then uses these signals to produce a three-dimensional image. A higher frequency alternating magnetic field enhances the sensitivity of signal detection. In compact devices designed for testing on small animals such as mice, which have already been commercialized, frequencies of approximately 25 kHz are used. One of the factors that hitherto hindered the practical application of this system in the treatment of humans was the extremely large size of the power supply unit needed to drive the much larger coil. By leveraging its extensive electromagnetic technology know-how acquired through the development of various devices, and by fine-tuning the configuration of the coils that generate alternating magnetic fields and those dedicated to signal detection, Mitsubishi Electric has developed a process that minimizes extraneous signals (noise) that hinder the detection of magnetic signals. As a result, we have succeeded in developing a magnetic particle imaging device that can sensitively image magnetic particles in an area equivalent to the size of the human brain
An optical temperature measurement method based on Magneto-optical Kerr Effect of metal nanofilms
No full textIn this study, we demonstrate a novel magneto-optical thermometer using a Magneto-optical Kerr Effect (MOKE) system optimally configured with a photoelastic modulator (PEM) that combines the optical and pyro effects of magnetic metal nanofilms to detect transient surface temperatures with high sensitivity and temporal resolution. The temperature-induced Kerr signal of the metal nanofilms is finally transformed into the AC-DC harmonic ratio. By innovatively configuring the analyzer axis close to the extinction position, the signal gain of the harmonic ratio can be increased while reducing the background signal, thus significantly improving the SNR of the temperature measurement. This magneto-optical thermometer combines the high spatial and temporal resolution of MOKE to provide a possible method for non-invasive and fast temperature measurements on the micro- and nanometer scales, and is expected to be useful in temperature imaging applications in conjunction with optical imaging techniques
A Human-Scale Magnetic Particle Imaging System for Functional Neuroimaging
No full textNon-invasive neuroimaging techniques have enabled a paradigm shift in the way neuroscientists study the human brain. However, the sensitivity limitations of existing methods are a barrier to the identification of differences in brain function in disease states in individuals, as required for clinical use. In contrast, conventional neuroscience studies can average across large cohorts (up to 100s of subjects) to discern significant differences. Magnetic Particle Imaging is naturally sensitive to changes in hemodynmaic blood volume associated with brain activation and may overcome the sensitivity barrier to clinical use. The sensitivity of MPI stems from the strong magnetic moment that induces the signal paired with an elimination of biological background signals and their associated biological nuisance fluctuations ("physiological noise"). However, MPI instrumentation is not widely available at the human scale, especially for the time-series imaging required for functional studies. Here, we demonstrate the sensitivity of a human-scale field-free line MPI system capable of long-term time series imaging at a 5 second temporal resolution and a spatial resolution of 6 mm, with a detection limit of 150 ng Fe (at SNR = 1). We hope this step toward human fMPI provides the sensitivity to enable new directions in neuroimaging, particularly permitting diagnostic functional neuroimaging of diseases states