@article{Foerger2026IEEESensors, Author = {F. Foerger, M. Boberg, N. Hackelberg, P. Heinisch, K. Ostaszewski, J. Faltinath, P. Suskin, F. Thieben, F. Mohn, P. Jürß, M. Möddel and T. Knopp}, Title = {3-D Magnetic Field Camera With Subsecond Temporal Resolution.}, Journal = {IEEE Sensors Journal.}, Year = {(2026).}, Volume = {26.}, Number = {(1),}, Note = {article}, Doi = {https://doi.org/10.1109/JSEN.2025.3629803}, Url = {https://ieeexplore.ieee.org/document/11244237}, Abstract = {Accurate and efficient volumetric magnetic field measurements are essential for a wide range of applications. Conventional methods are often limited in terms of measurement speed and applicability or suffer from scaling problems at larger volumes. This work presents a proof-of-concept field camera designed to measure magnetic fields within a spherical volume at a frame rate of 10 Hz. The camera features an array of 3-D Hall magnetometers positioned according to a spherical t-design, allowing simultaneous magnetic field data acquisition from the surface of the sphere. The approach enables the efficient representation of all three components of the magnetic field inside the sphere using a sixth-degree polynomial, significantly reducing measurement time compared with sequential methods. This work details the design, calibration, and measurement methods of the field camera. To evaluate its performance, we compare it with a sequential single-sensor measurement by examining a magnetic gradient field. The obtained measurement uncertainties of approximately 1% demonstrate the feasibility of the approach and its potential applicability to a variety of future applications.} } @article{scheffler2025efficient, Author = {K. Scheffler, L. Meyn, F. Foerger, M. Boberg, M. Möddel, and T. Knopp}, Title = {Efficient measurement and representation of magnetic fields in tomographic imaging using ellipsoidal harmonics.}, Journal = {Communications Physics.}, Year = {(2025).}, Volume = {8.}, Number = {(112),}, Month = {January}, Note = {article, openaccess, magneticfield}, Publisher = {Nature:}, Doi = {10.1038/s42005-025-02012-5}, Keywords = {magnetic resonance imaging, magnetic particle imaging, magneticfield }, Abstract = {Given the pivotal role of magnetic fields in modern medicine, there is an increasing necessity for a precise characterization of their strength and orientation at high spatial and temporal resolution. As source-free magnetic fields present in tomographic imaging can be described by harmonic polynomials, they can be efficiently represented using spherical harmonic expansions, which allows for measurement at a small set of points on a sphere surrounding the field of view. However, the majority of closed-bore systems possess a cylindrical field of view, making a sphere an inadequate choice for coverage. Ellipsoids represent a superior geometrical choice, and the theory of ellipsoidal harmonic expansions can be applied to magnetic fields in an analogous manner. Despite the mathematical principles underpinning ellipsoidal harmonics being well-established, their utilization in practical applications remains relatively limited. In this study, we present an effective and flexible approach to measuring and representing magnetic fields present in tomographic imaging, which draws upon the theory of ellipsoidal harmonic expansions.} } @article{boberg2025SHE, Author = {M. Boberg, T. Knopp, and M. Möddel}, Title = {Unique compact representation of magnetic fields using truncated solid harmonic expansions.}, Journal = {European Journal of Applied Mathematics.}, Year = {(2025).}, Pages = {1-28}, Month = {Jan}, Note = {article, magneticfield, openaccess}, Doi = {10.1017/S0956792524000883}, Url = {https://www.cambridge.org/core/journals/european-journal-of-applied-mathematics/article/unique-compact-representation-of-magnetic-fields-using-truncated-solid-harmonic-expansions/4654E5547EE13A3894CD42342782231C#article}, Abstract = {Precise knowledge of magnetic fields is crucial in many medical imaging applications such as magnetic resonance imaging (MRI) or magnetic particle imaging (MPI), as they form the foundation of these imaging systems. Mathematical methods are essential for efficiently analysing the magnetic fields in the entire field-of-view. In this work, we propose a compact and unique representation of the magnetic fields using real solid spherical harmonic expansions, which can be obtained by spherical t-designs. To ensure a unique representation, the expansion point is shifted at the level of the expansion coefficients. As an application scenario, these methods are used to acquire and analyse the magnetic fields of an MPI system. Here, the field-free-point of the spatial encoding field serves as the unique expansion point.} } @article{Foerger2024AIS, Author = {F. Foerger, M. Boberg, J. Faltinath, T. Knopp, M. Möddel}, Title = {Design and Optimization of a Magnetic Field Generator for Magnetic Particle Imaging with Soft Magnetic Materials.}, Journal = {Advanced Intelligent Systems.}, Year = {(2024).}, Volume = {6.}, Number = {(11),}, Note = {article}, Doi = {https://doi.org/10.1002/aisy.202400017}, Url = {https://advanced.onlinelibrary.wiley.com/doi/full/10.1002/aisy.202400017}, Abstract = {Magnetic field generators are a key component of Magnetic Particle Imaging (MPI) systems, and their power consumption is a major obstacle on the path to human-sized scanners. Despite their importance, a focused discussion of these generators is rare, and a comprehensive description of the design process is currently lacking. This work presents a methodology for the design and optimization of selection field generators operating with soft magnetic materials outside the linear regime in the context of MPI. Key elements are a mathematical model of magnetic field generators, a formalism for defining field sequences, and a relationship between power consumption and field sequence. These are used to define the design space of a field generator given its system requirements and constraints. The design process is then formulated as an optimization problem. Subsequently, this methodology is then utilized to design a new magnetic field generator specifically for cerebral imaging studies. The optimization result outperforms our existing MPI field generator in terms of power consumption and field of view size, providing a proof-of-concept for the entire methodology. As the approach is very general, it can be extended beyond the MPI context to other areas such as magnetic manipulation of medical devices and micro-robotics.} } @article{thieben_system_2024, Author = {F. Thieben, F. Foerger, F. Mohn, N. Hackelberg, M. Boberg, J.-P. Scheel, Möddel, M. Graeser, and T. Knopp}, Title = {System Characterization of a Human-Sized 3D Real-Time Magnetic Particle Imaging Scanner for Cerebral Applications.}, Journal = {Communications Engineering.}, Year = {(2024).}, Volume = {3.}, Number = {(1),}, Pages = {47}, Note = {article, openaccess, brainimager}, Doi = {10.1038/s44172-024-00192-6}, Keywords = {Mohn}, Abstract = {Abstract Since the initial patent in 2001, the Magnetic Particle Imaging community has endeavored to develop a human-applicable Magnetic Particle Imaging scanner, incorporating contributions from various research fields. Here we present an improved head-sized Magnetic Particle Imaging scanner with low power consumption, operated by open-source software and characterize it with an emphasis on human safety. The focus is on the evaluation of the technical components and on phantom experiments for brain perfusion. We achieved 3D single- and multi-contrast imaging at 4 Hz frame rate. The system characterization includes sensitivity, resolution, perfusion and multi-contrast experiments as well as field measurements and sequence analysis. Images were acquired with a clinically approved tracer and within human peripheral nerve stimulation thresholds. This advanced scanner holds potential as a tomographic imager for diagnosing conditions such as ischemic stroke (different stages) or intracranial hemorrhage in environments lacking electromagnetic shielding, such as the intensive care unit.} } @article{scheffler2024solving, Author = {K. Scheffler, M. Boberg, and T. Knopp}, Title = {Solving the MPI reconstruction problem with automatically tuned regularization parameters.}, Journal = {Physics in Medicine & Biology.}, Year = {(2024).}, Volume = {69.}, Number = {(4),}, Month = {January}, Note = {article, openaccess}, Doi = {10.1088/1361-6560/ad2231}, Keywords = {Image reconstruction, magnetic particle imaging, regularization }, Abstract = {In the field of medical imaging, Magnetic Particle Imaging (MPI) poses a promising non-ionizing tomographic technique with high spatial and temporal resolution. In MPI, iterative solvers are used to reconstruct the particle distribution out of the measured voltage signal based on a system matrix. The amount of regularization needed to reconstruct an image of good quality differs from measurement to measurement, depending on the MPI system and the measurement settings. Finding the right choice for the three major parameters controlling the regularization is commonly done by hand and requires time and experience. In this work, we study the reduction to a single regularization parameter and propose a method that enables automatic reconstruction. The method is qualitatively and quantitatively validated on several MPI data sets showing promising results.} } @article{Thieben2023receive, Author = {F. Thieben, T. Knopp, M. Boberg, F. Foerger, M.Graeser, and M. Möddel}, Title = {On the Receive Path Calibration of Magnetic Particle Imaging Systems.}, Journal = {IEEE Transactions on Instrumentation and Measurement.}, Year = {(2023).}, Volume = {72.}, Pages = {1-15}, Note = {article, instrumentation}, Doi = {10.1109/TIM.2022.3219461}, Url = {https://ieeexplore.ieee.org/document/9939022}, Abstract = {Magnetic nanoparticles are a valuable tool in many biomedical applications and can be used for diagnostic and therapeutic purposes. In magnetic particle imaging (MPI) and magnetic particle spectroscopy (MPS), the particles are subjected to a dynamic magnetic field and the particle magnetization response is simultaneously measured using one or multiple receive coils. Separating the particle signal from the feed-through signal is commonly done by advanced passive filtering, which distorts the particle signal. To correct this distortion, the transfer function of the receive chain needs to be known. While in principle, the transfer function can be simulated, due to imperfections in the electronic components, it is often more accurate to determine the transfer function in a calibration procedure. Although this system calibration, utilizing a calibration-coil setup has been done by several research groups in the past, a general description of the underlying calibration model and methodology is still missing. In this paper we provide a general multi-channel calibration procedure for inductive receive paths in MPI and a blueprint to investigate model and method uncertainties. We generalized the calibration procedure to also cover non-orthogonal and non-homogeneous receive coils. Finally, we showcase the calibration procedure and uncertainty analysis on our custom MPS system and use the MPI transfer functions of misaligned receive coils to decouple their superimposed receive signals from the receive path. The findings enable the comparison of MPI signals from different devices and can be used to normalize measurements and system functions in devices with exchangeable receive coils.} } @article{scheffler2022extrapolation, Author = {K. Scheffler, M. Boberg, and T. Knopp}, Title = {Extrapolation of System Matrices in Magnetic Particle Imaging.}, Journal = {IEEE Transactions on Medical Imaging.}, Year = {(2023).}, Volume = {42.}, Number = {(4),}, Pages = { 1121 - 1132}, Month = {April}, Note = {article, multi-patch, artifact, openaccess}, Doi = {10.1109/TMI.2022.3224310}, Keywords = {Image reconstruction, magnetic particle imaging, multi-patch MPI, system-matrix extrapolation }, Abstract = {Magnetic particle imaging exploits the non-linear magnetization of superparamagnetic iron-oxide particles to generate a tomographic image in a defined field-of-view. For reconstruction of the particle distribution, a time-consuming calibration step is required, in which system matrices get measured using a robot. To achieve artifact-free images, system matrices need to cover not only the field-of-view but also a larger area around it. Especially for large measurements – inevitable for future clinical application – this leads to long calibration time and high consumption of persistent memory. In this work, we analyze the signal in the outer part of the system matrix and motivate the usage of extrapolation methods to computationally expand the system matrix after restricting the calibration to the field-of-view. We propose a suitable extrapolation method and show its applicability on measured 2D and 3D data. In doing so, we achieve a considerable reduction of calibration time and consumption of persistent memory while preserving an artifact-free result.} } @article{Knopp2023NFFT, Author = {T. Knopp, M. Boberg, and M. Grosser}, Title = {NFFT.jl: Generic and Fast Julia Implementation of the Nonequidistant Fast Fourier Transform.}, Journal = {SIAM Journal on Scientific Computing.}, Year = {(2023).}, Volume = {45.}, Number = {(3),}, Pages = {C179-C205}, Note = {article, opensoftware, openaccess, generalsoftware}, Doi = {10.1137/22M1510935}, Url = {https://arxiv.org/abs/2208.00049}, Keywords = {article}, Abstract = {The nonequidistant fast Fourier transform (NFFT) is an extension of the famous fast Fourier transform (FFT) that can be applied to nonequidistantly sampled data in time/space or frequency domain. It is an approximative algorithm that allows one to control the approximation error in such a way that machine precision is reached while keeping the algorithmic complexity in the same order as a regular FFT. The NFFT plays a major role in many signal processing applications and has been intensively studied from a theoretical and computational perspective. The fastest CPU implementations of the NFFT are implemented in the low-level programming languages C and C++ and require a compromise between code generalizability, code readability, and code efficiency. The programming language Julia promises new opportunities in optimizing these three conflicting goals. In this work we show that Julia indeed allows one to develop an NFFT implementation which is completely generic and dimension-agnostic and requires about two to three times less code than the other famous libraries NFFT3 and FINUFFT while still being one of the fastest NFFT implementations developed to date.} } @article{Mohn2022pulsed, Author = {F. Mohn, T. Knopp, M. Boberg, F. Thieben, P. Szwargulski, and M. Graeser}, Title = {System Matrix Based Reconstruction for Pulsed Sequences in Magnetic Particle Imaging.}, Journal = {IEEE Transactions on Medical Imaging.}, Year = {(2022).}, Volume = {41.}, Number = {(7),}, Pages = {1862-1873}, Month = {July}, Note = {article, instrumentation}, Doi = {10.1109/TMI.2022.3149583}, Url = {https://ieeexplore.ieee.org/document/9706173}, Abstract = {Improving resolution and sensitivity will widen possible medical applications of magnetic particle imaging. Pulsed excitation promises such benefits, at the cost of more complex hardware solutions and restrictions on drive field amplitude and frequency. State-of-the-art systems utilize a sinusoidal excitation to drive superparamagnetic nanoparticles into the non-linear part of their magnetization curve, which creates a spectrum with a clear separation of direct feed-through and higher harmonics caused by the particles response. One challenge for rectangular excitation is the discrimination of particle and excitation signals, both broad-band. Another is the drive-field sequence itself, as particles that are not placed at the same spatial position, may react simultaneously and are not separable by their signal phase or shape. To overcome this potential loss of information in spatial encoding for high amplitudes, a superposition of shifting fields and drive-field rotations is proposed in this work. Upon close view, a system matrix approach is capable to maintain resolution, independent of the sequence, if the response to pulsed sequences still encodes information within the phase. Data from an Arbitrary Waveform Magnetic Particle Spectrometer with offsets in two spatial dimensions is measured and calibrated to guarantee device independence. Multiple sequence types and waveforms are compared, based on frequency space image reconstruction from emulated signals, that are derived from measured particle responses. A resolution of 1.0 mT (0.8 mm for a gradient of (−1.25,−1.25,2.5) T/m ) in x- and y-direction was achieved and a superior sensitivity for pulsed sequences was detected on the basis of reference phantoms.} } @article{albers2022modeling, Author = {H. Albers, T. Knopp, M. Möddel, M. Boberg, and T. Kluth}, Title = {Modeling the magnetization dynamics for large ensembles of immobilized magnetic nanoparticles in multi-dimensional magnetic particle imaging.}, Journal = {Journal of Magnetism and Magnetic Materials.}, Year = {(2022).}, Volume = {543.}, Pages = {168534}, Month = {February}, Note = {article, model-based}, Doi = {10.1016/j.jmmm.2021.168534}, Url = {https://arxiv.org/abs/2106.08040}, Abstract = {Magnetic nanoparticles (MNPs) play an important role in biomedical applications including imaging modalities such as magnetic resonance imaging (MRI) and magnetic particle imaging (MPI). The latter one exploits the non-linear magnetization response of a large ensemble of magnetic nanoparticles to magnetic fields which allows determining the spatial distribution of the MNP concentration from measured voltage signals. The image-to-voltage mapping is linear and described by a system matrix. Currently, modeling the voltage signals of large ensembles of MNPs in an MPI environment is not yet accurately possible, especially for liquid tracers in multi-dimensional magnetic excitation fields. As an immediate consequence, the system matrix is still obtained in a time consuming calibration procedure. While the ferrofluidic case can be seen as the typical setting, more recently immobilized and potentially oriented MNPs have received considerable attention. By aligning the particles magnetic easy axis during immobilization one can encode the angle of the particle’s magnetic easy axis into the magnetization response providing a relevant benchmark system for model-based approaches. In this work we address the modeling problem for immobilized and oriented MNPs in the context of MPI. We investigate a model-based approach where the magnetization response is simulated by a Néel rotation model for the particle’s magnetic moments and the ensemble magnetization is obtained by solving a Fokker–Planck equation approach. Since the parameters of the model are a-priori unknown, we investigate different methods for performing a parameter identification and discuss two different models: One where a single function vector is used from the space spanned by the model parameters and another where a superposition of function vectors is considered. We show that our model can much more accurately reproduce the orientation dependent signal response when compared to the equilibrium model, which marks the current state-of-the-art for model-based system matrix simulations in MPI.} } @article{Zdun2022joint, Author = {L. Zdun, M. Boberg, and C. Brandt}, Title = {Joint multi-patch reconstruction: fast and improved results by stochastic optimization.}, Journal = {International Journal on Magnetic Particle Imaging.}, Year = {(2022).}, Volume = {8.}, Number = {(2),}, Pages = {1-8}, Note = {article, multi-patch, artifact, openaccess}, Doi = {10.18416/IJMPI.2022.2212002}, Url = {https://journal.iwmpi.org/index.php/iwmpi/article/view/477}, Abstract = {In order to measure larger volumes in magnetic particle imaging, it is necessary to divide the region of interest into several patches and measure those patches individually due to a limited size of the field of view. This procedure yields truncation artifacts at the patches boundaries during reconstruction. Applying a regularization which takes into account neighbourhood structures not only on one patch but across all patches can significantly reduce those artifacts. However, the current state-of-the-art reconstruction method using the Kaczmarz algorithm is limited to Tikhonov regularization. We thus propose to use the stochastic primal-dual hybrid gradient method to solve the multi-patch reconstruction task. Our experiments show that the quality of our reconstructions is significantly higher than those obtained by Tikhonov regularization and Kaczmarz method. Moreover, using our proposed method, a joint reconstruction considerably reduces the computational costs compared to multiple single-patch reconstructions. The algorithm proposed is thus competitive to the current state-of-the-art method not only regarding reconstruction quality but also concerning the computational effort.} } @article{boberg2021dynamicrange, Author = {M. Boberg, N. Gdaniec, P. Szwargulski, F. Werner, M. Möddel, and T. Knopp}, Title = {Simultaneous imaging of widely differing particle concentrations in MPI: problem statement and algorithmic proposal for improvement.}, Journal = {Physics in Medicine & Biology.}, Year = {(2021).}, Volume = {66.}, Number = {(9),}, Pages = {095004}, Month = {April}, Note = {article, artifact, openaccess}, Doi = {10.1088/1361-6560/abf202}, Url = {https://arxiv.org/abs/2205.01364}, Abstract = {Magnetic Particle Imaging (MPI) is a tomographic imaging technique for determining the spatial distribution of superparamagnetic nanoparticles. Current MPI systems are capable of imaging iron masses over a wide dynamic range of more than four orders of magnitude. In theory, this range could be further increased using adaptive amplifiers, which prevent signal clipping. While this applies to a single sample, the dynamic range is severely limited if several samples with different concentrations or strongly inhomogeneous particle distributions are considered. One scenario that occurs quite frequently in pre-clinical applications is that a highly concentrated tracer bolus in the vascular system shadows nearby organs with lower effective tracer concentrations. The root cause of the problem is the ill-posedness of the MPI imaging operator, which requires regularization for stable reconstruction. In this work, we introduce a simple two-step algorithm that increases the dynamic range by a factor of four. Furthermore, the algorithm enables spatially adaptive regularization, i.e. highly concentrated signals can be reconstructed with maximum spatial resolution, while low concentrated signals are strongly regularized to prevent noise amplification.} } @article{boberg2019generalized, Author = {M. Boberg, T. Knopp, P. Szwargulski, and M. Möddel}, Title = {Generalized MPI Multi-Patch Reconstruction using Clusters of similar System Matrices.}, Journal = {IEEE Transactions on Medical Imaging.}, Year = {(2020).}, Volume = {39.}, Number = {(5),}, Pages = {1347-1358}, Month = {May}, Note = {article, multi-patch, artifact, magneticfield, openaccess}, Doi = {10.1109/TMI.2019.2949171}, Url = {https://arxiv.org/abs/2205.01083}, Keywords = {calibration;image reconstruction;matrix algebra;medical image processing;tomographic imaging method magnetic particle imaging;stepwise spatial shift;MPI system matrix;image reconstruction;shift invariance;multipatch measurement sequence;image quality;MPI multipatch reconstruction;magnetic-field-based metric;multipatch reconstruction;continuous spatial shift;Image reconstruction;Calibration;Magnetic resonance imaging;Reconstruction algorithms;Atmospheric measurements;Particle measurements;Biomedical imaging;focus fields;image reconstruction;magnetic particle imaging}, Abstract = {The tomographic imaging method magnetic particle imaging (MPI) requires a multi-patch approach for capturing large field of views. This approach consists of a continuous or stepwise spatial shift of a small sub-volume of only few cubic centimeters size, which is scanned using one or multiple excitation fields in the kHz range. Under the assumption of ideal magnetic fields, the MPI system matrix is shift invariant and in turn a single matrix suffices for image reconstruction significantly reducing the calibration time and reconstruction effort. For large field imperfections, however, the method can lead to severe image artifacts. In the present work we generalize the efficient multi-patch reconstruction to work under non-ideal field conditions, where shift invariance holds only approximately for small shifts of the sub-volume. Patches are clustered based on a magnetic-field-based metric such that in each cluster the shift invariance holds in good approximation. The total number of clusters is the main parameter of our method and allows to trade off calibration time and image artifacts. The magnetic-field-based metric allows to perform the clustering without prior knowledge of the system matrices. The developed reconstruction algorithm is evaluated on a multi-patch measurement sequence with 15 patches, where efficient multi-patch reconstruction with a single calibration measurement leads to strong image artifacts. Analysis reveals that calibration measurements can be decreased from 15 to 11 with no visible image artifacts. A further reduction to 9 is possible with only slight degradation in image quality.} } @article{gdaniec2020rotation, Author = {N. Gdaniec, M. Boberg, M. Möddel, P. Szwargulski, and T. Knopp}, Title = {Suppression of Motion Artifacts Caused by Temporally Recurring Tracer Distributions in Multi-Patch Magnetic Particle Imaging.}, Journal = {IEEE Transactions on Medical Imaging.}, Year = {(2020).}, Volume = {39.}, Number = {(11),}, Pages = {3548-3558}, Month = {November}, Note = {article, multi-patch, artifact, opendata, openaccess}, Doi = {10.1109/TMI.2020.2998910}, Url = {https://arxiv.org/abs/2205.01085}, Keywords = {Image reconstruction;Motion artifacts;Dynamics;Phantoms;Spatial resolution;Biomedical imaging;magnetic particle imaging;motion artifacts;motion compensation;motion detection}, Abstract = {Magnetic particle imaging is a tracer based imaging technique to determine the spatial distribution of superparamagnetic iron oxide nanoparticles with a high spatial and temporal resolution. Due to physiological constraints, the imaging volume is restricted in size and larger volumes are covered by shifting object and imaging volume relative to each other. This results in reduced temporal resolution, which can lead to motion artifacts when imaging dynamic tracer distributions. A common source of such dynamic distributions are cardiac and respiratory motion in in-vivo experiments, which are in good approximation periodic. We present a raw data processing technique that combines data snippets into virtual frames corresponding to a specific state of the dynamic motion. The technique is evaluated on the basis of measurement data obtained from a rotational phantom at two different rotational frequencies. These frequencies are determined from the raw data without reconstruction and without an additional navigator signal. The reconstructed images give reasonable representations of the rotational phantom frozen in several different states of motion while motion artifacts are suppressed.} } @article{Graeser2019b, Author = {M. Graeser, F. Thieben, P. Szwargulski, F. Werner, N. Gdaniec, M. Boberg, F. Griese, M. Möddel, P. Ludewig, D. van de Ven, O.M. Weber, O. Woywode, B. Gleich, and T. Knopp}, Title = {Human-sized Magnetic Particle Imaging for Brain Applications.}, Journal = {Nature Communications.}, Year = {(2019).}, Volume = {10.}, Number = {(1936),}, Pages = {1-9}, Note = {article, brainimager, openaccess}, Doi = {10.1038/s41467-019-09704-x}, Url = {https://www.nature.com/articles/s41467-019-09704-x}, Keywords = {article}, Abstract = {Determining the brain perfusion is an important task for diagnosis of vascular diseases such as occlusions and intracerebral haemorrhage. Even after successful diagnosis, there is a high risk of restenosis or rebleeding such that patients need intense attention in the days after treatment. Within this work, we present a diagnostic tomographic imager that allows access to brain perfusion quantitatively in short intervals. The device is based on the magnetic particle imaging technology and is designed for human scale. It is highly sensitive and allows the detection of an iron concentration of 263 pmol(Fe)/ml, which is one of the lowest iron concentrations imaged by MPI so far. The imager is self-shielded and can be used in unshielded environments such as intensive care units. In combination with the low technical requirements this opens up a variety of medical applications and would allow monitoring of stroke on intensive care units.} } @article{knopp2019mpifiles, Author = {T. Knopp, M. Möddel, F. Griese, F. Werner, P. Szwargulski, N. Gdaniec, and M. Boberg}, Title = {MPIFiles.jl: A Julia Package for Magnetic Particle Imaging Files.}, Journal = {Journal of Open Source Software.}, Year = {(2019).}, Volume = {4.}, Number = {(38),}, Pages = {1331}, Note = {article, opensoftware, openaccess, mpisoftware}, Doi = {https://doi.org/10.21105/joss.01331}, Url = {http://joss.theoj.org/papers/10.21105/joss.01331} } @article{Knopp2019MPIReco, Author = {T. Knopp, P. Szwargulski, F. Griese, M. Grosser, M. Boberg, and M. Möddel}, Title = {MPIReco.jl: Julia Package for Image Reconstruction in MPI.}, Journal = {International Journal on Magnetic Particle Imaging.}, Year = {(2019).}, Volume = {5.}, Number = {(1),}, Pages = {9 pp}, Note = {article, opensoftware, openaccess, mpisoftware}, Doi = {10.18416/ijmpi.2019.1907001}, Keywords = {article} } @COMMENT{Bibtex file generated on 2026-5-13 with typo3 si_bibtex plugin. Data from https://www.tuhh.de/ibi/people/marija-boberg }