Tobias Knopp

• Prof. Dr.-Ing.
• Professor at University Medical Center Hamburg - Eppendorf

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 the development of a magnetometer array designed to measure magnetic fields within...

The precise derivation of physical quantities like temperature or pressure at arbitrary locations is useful in numerous contexts, e.g. medical procedures or industrial process engineering. The novel sensor technology of magneto-mechanical resonators (MMR), based on the interaction of a rotor and stator permanent magnet, allows for the combined trac...

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 custom-developed magneto-mechanical resonator (MMR) for wireless pressure measurement is investigated for potential applications in process engineering. The MMR sensor utilises changes in the resonance frequency caused by pressure on a flexible 3D printed membrane. The thickness of the printed membrane plays a crucial role in determining the perf...

The phase problem is a well known ill-posed reconstruction problem of coherent lens-less microscopic imaging, where only the intensities of a complex wave-field are measured by the detector and the phase information is lost. For the reconstruction of sharp images from holograms in a near-field experimental setting, it is crucial to solve the autofo...

Passive wireless sensors are crucial in modern medical and industrial settings to monitor procedures and conditions. We demonstrate a circuit to inductively excite passive resonators and to conduct their decaying signal response to a low noise amplifier. Two design variations of a generic transmit-receive signal chain are proposed, measured, and de...

Magnetic Particle Imaging (MPI) is an emerging imaging modality based on the magnetic response of superparamagnetic iron oxide nanoparticles to achieve high-resolution and real-time imaging without harmful radiation. One key challenge in the MPI image reconstruction task arises from its underlying noise model, which does not fulfill the implicit Ga...

Determining the position and orientation of a medical instrument is essential for accurate procedures in endoscopy, surgery, and vascular interventions. Recently, a novel sensor based on torsional pendulum-like magneto-mechanical motion has been proposed. This sensor is passive, wireless and inductively coupled to a transmit-receive coil array. Thi...

Magnetic particle imaging is a tracer-based tomographic imaging technique that allows the concentration of magnetic nanoparticles to be determined with high spatio-temporal resolution. To reconstruct an image of the tracer concentration, the magnetization dynamics of the particles must be accurately modeled. A popular ensemble model is based on sol...

Objective. Magnetic particle imaging (MPI) is a tracer-based medical imaging modality with great potential due to its high sensitivity, high spatiotemporal resolution, and ability to quantify the tracer concentration. Image reconstruction in MPI is an ill-posed problem, which the use of regularization methods can address. Multi-contrast MPI reconst...

Magnetic particle imaging (MPI) is a trending tracer imaging technique relatively newly proposed. In MPI, a time-consuming system matrix calibration scan is required to reconstruct the spatial distribution of superparamagnetic nanoparticles. Compressed sensing (CS) techniques are widely utilized to reduce the time required for system matrix calibra...

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 me...

Purpose: The trend towards lower radiation doses and advances in computed tomography (CT) reconstruction may impair the operation of pretrained segmentation models, giving rise to the problem of estimating the dose robustness of existing segmentation models. Previous studies addressing the issue suffer either from a lack of registered low- and ful...

Objective. The availability of magnetic nanoparticles (MNPs) with medical approval for human intervention is fundamental to the clinical translation of magnetic particle imaging (MPI). In this work, we thoroughly evaluate and compare the magnetic properties of an magnetic resonance imaging (MRI) approved tracer to validate its performance for MPI i...

Objectives Opposed to other spectral CT techniques, fat quantification in dual-layer detector CT (dlCT) has only recently been developed. The impact of concomitant iron overload and dlCT-specific protocol settings such as the dose right index (DRI), a measure of image noise and tube current, on dlCT fat quantification was unclear. Further, spectral...

In magnetic particle imaging, a field-free region is maneuvered throughout the field of view using a time-varying magnetic field known as the drive-field. Human-sized systems operate the drive-field in the kHz range and generate it by utilizing strong currents that can rise to the kA range within a coil called the drive field generator. Matching an...

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...

The phase problem is a well known ill-posed reconstruction problem of coherent lens-less microscopic imaging, where only the squared magnitude of a complex wavefront is measured by a detector while the phase information of the wave field is lost. To retrieve the lost information, common algorithms rely either on multiple data acquisitions under var...

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 a...

Gastrointestinal bleeding, as a potentially life-threatening condition, is typically diagnosed by radiation-based imaging modalities like computed tomography or more invasively catheter-based angiography. Endoscopy enables examination of the upper gastrointestinal tract and the colon but not of the entire small bowel. Magnetic Particle Imaging (MPI...

Objective.Magnetic particle imaging (MPI) is capable of high temporal resolution measurements of the spatial distribution of magnetic nanoparticles and therefore well suited for perfusion imaging, which is an important tool in medical diagnosis. Perfusion imaging in MPI usually requires a fresh bolus of tracer material to capture the key signal dyn...

Various imaging modalities allow for time-dependent image reconstructions from measurements where its acquisition also has a time-dependent nature. Magnetic particle imaging (MPI) falls into this class of imaging modalities and it thus also provides a dynamic inverse problem. Without proper consideration of the dynamic behavior, motion artifacts in...

Machine learning techniques that perform morphological classification of astronomical sources often suffer from a scarcity of labelled training data. Here, we focus on the case of supervised deep learning models for the morphological classification of radio galaxies, which is particularly topical for the forthcoming large radio surveys. We demonstr...

Magnetic Particle Imaging is capable to measure the spatial distribution of magnetic nanoparticles with high temporal resolution. As a quantitative tracer based imaging method, the signal is linear in the tracer concentration for any location that contains nanoparticles and zero in the surrounding tissue which does not provide any intrinsic signal....

Precise knowledge of magnetic fields is crucial in many medical imaging applications like magnetic resonance imaging or magnetic particle imaging (MPI) as they are the foundation of these imaging systems. For the investigation of the influence of field imperfections on imaging, a compact and unique representation of the magnetic fields using real s...

Machine learning techniques that perform morphological classification of astronomical sources often suffer from a scarcity of labelled training data. Here, we focus on the case of supervised deep learning models for the morphological classification of radio galaxies, which is particularly topical for the forthcoming large radio surveys. We demonstr...

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, sy...

In the above article [1] , there is an error in Section III-D regarding the unit of the added noise level on page 1868, second paragraph. It should say “to select a noise level of $n^{r}$ = $70\cdot 10^{-15}$ Am <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> .”

Vascular interventions are a promising application of Magnetic Particle Imaging enabling a high spatial and temporal resolution without using ionizing radiation. The possibility to visualize the vessels as well as the devices, especially at the same time using multi-contrast approaches, enables a higher accuracy for diagnosis and treatment of vascu...

The non-equidistant fast Fourier transform (NFFT) is an extension of the famous fast Fourier transform (FFT), which can be applied to non-equidistantly sampled data in time/space or frequency domain. It is an approximative algorithm that allows to control the approximation error in such a way that machine precision is reached while keeping the algo...

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 prev...

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 eac...

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...

Signal stability is crucial for an accurate diagnosis via magnetic particle imaging (MPI). However, MPI-tracer nanoparticles frequently agglomerate during their in vivo applications leading to particle interactions altering the signal....

Objectives: Fat quantification by dual-energy computed tomography (DECT) provides contrast-independent objective results, for example, on hepatic steatosis or muscle quality as parameters of prognostic relevance. To date, fat quantification has only been developed and used for source-based DECT techniques as fast kVp-switching CT or dual-source CT...

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 nanoparticle...

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 multi...

Tracer and thus signal stability is crucial for an accurate diagnosis via magnetic particle imaging (MPI). However, MPI-tracer nanoparticles frequently agglomerate during their in vivo applications leading to particle interactions. Here, we investigate the influence of such magnetic coupling phenomena on the MPI signal. We prepared and characterize...

Doses of irradiation above 25 kGy are known to cause irreversible mechanical decay in bone tissue. However, the impact of irradiation doses absorbed in a clinical setting on the mechanical properties of bone remains unclear. In daily clinical practice and research, patients and specimens are exposed to irradiation due to diagnostic imaging tools, w...

Advances in micromachinery and nanotechnology, such as magnetically actuated microrobots for navigating in viscous environments, are important driving forces in medicine. Recently, it has been shown that the spatial orientation of an ensemble of immobilized nanoparticles with parallel-aligned magnetic easy axes has an effect on the magnetization re...

Stroke is one of the leading worldwide causes of death and sustained disability. Rapid and accurate assessment of cerebral perfusion is essential to diagnose and successfully treat stroke patients. Magnetic particle imaging (MPI) is a new technology with the potential to overcome some limitations of established imaging modalities. It is an innovati...

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...

Magnetic nanoparticles and their magnetization dynamics play an important role in many applications. We focus on magnetization dynamics in large ensembles of single domain nanoparticles being characterized by either Brownian or Néel rotation mechanisms. Simulations of the respective behavior are obtained by solving advection–diffusion equations on...

Improving resolution and sensitivity will widen possible medical applications of magnetic particle imaging in its clinical application. Pulsed excitation promises such benefits, at the cost of more complex hardware solutions and restrictions on drive field amplitude and frequency. In this work, a sequence is proposed, that combines high drive-field...

Background signals are a primary source of artifacts in magnetic particle imaging and limit the sensitivity of the method since background signals are often not precisely known and vary over time. The state-of-the art method for handling background signals uses one or several background calibration measurements with an empty scanner bore and subtra...

Purpose Magnetic particle imaging (MPI) is a preclinical imaging technique capable of visualizing the spatio‐temporal distribution of magnetic nanoparticles. The image reconstruction of this fast and dynamic process relies on efficiently solving an ill‐posed inverse problem. Current approaches to reconstruct the tracer concentration from its measur...

Magnetic nanoparticles (MNPs) play an important role in biomedical applications including imaging modalities such as 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 conc...

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 prev...

Purpose The aim of this work is to develop a high‐performance, flexible, and easy‐to‐use MRI reconstruction framework using the scientific programming language Julia. Methods Julia is a modern, general purpose programming language with strong features in the area of signal/image processing and numerical computing. It has a high‐level syntax but st...

Die Magnetpartikelbildgebung (MPI) ist eine junge tomographische Bildgebungstechnik, die magnetische Nanopartikel mit einer hohen räumlichen und zeitlichen Auflösung quantitativ abbildet. Eine gängige Methode zur Rekonstruktion von MPI-Daten ist die Systemmatrix (SM)-basierte Rekonstruktion. Die komplexwertige SM wird in einer zeitaufwändigen Kalib...

Purpose: The aim of this work is to develop a high-performance, flexible and easy-to-use MRI reconstruction framework using the scientific programming language Julia. Methods: Julia is a modern, general purpose programming language with strong features in the area of signal / image processing and numerical computing. It has a high-level syntax but...

Objective The aim is to evaluate whether smart worklist prioritization by artificial intelligence (AI) can optimize the radiology workflow and reduce report turnaround times (RTATs) for critical findings in chest radiographs (CXRs). Furthermore, we investigate a method to counteract the effect of false negative predictions by AI—resulting in an ext...

Magnetic Particle Imaging (MPI) is a novel and versatile imaging modality developing towards human application. When up-scaling to human size, the sensitivity of the systems naturally drops as the coil sensitivity depends on the bore diameter. Thus, new methods to push the sensitivity limit further have to be investigated to cope for this loss. In...

Magnetic nanoparticles and their magnetization dynamics play an important role in many applications. We focus on magnetization dynamics in large ensembles of single domain nanoparticles being characterized by either Brownian or N\'{e}el rotation mechanisms. Simulations of the respective behavior are obtained by solving advection-diffusion equations...

Magnetic particle imaging (MPI) data is commonly reconstructed using a system matrix acquired in a time-consuming calibration measurement. Compared to model-based reconstruction, the calibration approach has the important advantage that it takes into account both complex particle physics and system imperfections. However, this has the disadvantage...

Magnetic particle imaging (MPI) is an innovative radiation-free tomographic imaging method providing excellent temporal resolution, contrast, sensitivity, and safety. Mobile human MPI prototypes suitable for continuous bedside monitoring of whole-brain perfusion have been developed. However, for the clinical translation of MPI, a crucial gap in kno...

Although Magnetic Particle Imaging (MPI) is not yet in clinical use, it is highly promising for several medical applications , and especially for applications in diagnostic vascular in vivo imaging and imaging-guided vascular interventions. Furthermore, in the last years, different superparamagnetic iron oxide (SPIO) based contrast agents have been...

Background signals are a primary source of artifacts in magnetic particle imaging and limit the sensitivity of the method since background signals are often not precisely known and vary over time. The state-of-the art method for handling background signals uses one or several background calibration measurements with an empty scanner bore and subtra...

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 eac...

Temperature-resolved magnetic particle imaging (MPI) represents a promising tool for medical imaging applications. In this study an approach based on a single calibration measurement was applied for highlighting the potential of MPI for monitoring of temperatures during thermal ablation of liver tumors. For this purpose, liver tissue and liver tumo...

Magnetic Particle Imaging (MPI) is a novel and versatile imaging modality developing towards human application. When up-scaling to human size, the sensitivity of the systems naturally drops as the coil sensitivity depends on the bore diameter. Thus, new methods to push the sensitivity limit further have to be investigated to cope for this loss. In...

Purpose Using 4D magnetic particle imaging (MPI), intravascular optical coherence tomography (IVOCT) catheters are tracked in real time in order to compensate for image artifacts related to relative motion. Our approach demonstrates the feasibility for bimodal IVOCT and MPI in-vitro experiments. Material and methods During IVOCT imaging of a steno...

Magnetic Particle Imaging (MPI) is a preclinical imaging technique capable of visualizing the spatio-temporal distribution of magnetic nanoparticles. The image reconstruction of this fast and dynamic process relies on efficiently solving an ill-posed inverse problem. Current approaches to reconstruct the tracer concentration from its measurements a...

Aim: Magnetic particle imaging (MPI) is highly promising for biomedical applications, but optimal tracers for MPI, namely superparamagnetic iron oxide-based contrast agents, are still lacking. Materials & methods: The encapsulation of commercially available nanoparticles, specifically synomag ® -D and perimag ® , into human red blood cells (RBCs) w...

Growing radiologic workload and shortage of medical experts worldwide often lead to delayed or even unreported examinations, which poses a risk for patient's safety in case of unrecognized findings in chest radiographs (CXR). The aim was to evaluate, whether deep learning algorithms for an intelligent worklist prioritization might optimize the radi...

This is the version 1.0 of our static, 3D printable, anatomical rat model. The designed purpos is to provide a anatomical shaped phantom for medical imaging. The organs are constructed as hollow bodys, which can be filled with contrast agend suiteable for the technology of interest, e.g. iodine for CT, gadolinium for MRI or iron nanoparticles for M...

In Magnetic Particle Imaging (MPI), the system matrix plays an important role, as it encodes the relationship between particle concentration and the measured signal. Its acquisition requires a time-consuming calibration scan, whereas its size leads to a high memory-demand. Both of these aspects can be limiting factors in practice. In order to reduc...

Magnetic particle imaging is a tomographic imaging technique capable of measuring the local concentration of magnetic nanoparticles that can be used as tracers in biomedical applications. Since MPI is still at a very early stage of development, there are only a few MPI systems worldwide that are primarily operated by technical research groups that...

Purpose: Using 4D magnetic particle imaging (MPI), intravascular optical coherence tomography (IVOCT) catheters are tracked in real time in order to compensate for image artifacts related to relative motion. Our approach demonstrates the feasibility for bimodal IVOCT and MPI in-vitro experiments. Material and Methods: During IVOCT imaging of a sten...

Intravascular optical coherence tomography (IVOCT) is a catheter based image modality allowing for high resolution imaging of vessels. It is based on a fast sequential acquisition of A-scans with an axial spatial resolution in the range of 5 to 10 {\mu}m, i.e., one order of magnitude higher than in conventional methods like intravascular ultrasound...

Magnetic Particle Imaging (MPI) has been successfully used to visualize the distribution of superparamagnetic nanoparticles within 3D volumes with high sensitivity in real time. Since the magnetic field topology of MPI scanners is well suited for applying magnetic forces on particles and micron-sized ferromagnetic devices, MPI has been recently use...

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...

The image reconstruction problem of the tomographic imaging technique magnetic particle imaging (MPI) requires the solution of a linear inverse problem. One prerequisite for this task is that the imaging operator that describes the mapping between the tomographic image and the measured signal is accurately known. For 2D and 3D excitation patterns,...

For medical research, approximately 115 million animals are needed every year. Rodents are used to test possible applications and procedures for the diagnosis of anatomical and physiological diseases. However, working with living animals increases the complexity of an experiment. Accurate experimental planning is essential in order to fulfill the 3...

Purpose Magnetic particle imaging (MPI) is a novel tomographic radiation-free imaging technique that combines high spatial resolution and real-time capabilities, making it a promising tool to guide vascular interventions. Immediate availability of 3D image data is a major advantage over the presently used digital subtraction angiography (DSA), but...

Objective Magnetic Particle Imaging (MPI) is a new, fast and three-dimensional imaging technique, which is considered promising for angiographies. As available MPI-scanners suffer from restricted spatial resolution and are mostly constructed for small animal imaging, no vessels within one organ have been depicted by MPI, yet. The purpose of this st...

The image reconstruction problem of the tomographic imaging technique magnetic particle imaging (MPI) requires the solution of a linear inverse problem. One prerequisite for this task is that the imaging operator that describes the mapping between the tomographic image and the measured signal is accurately known. For 2D and 3D excitation patterns,...

Magnetic particle imaging (MPI) is a tracer-based imaging technique that can be used for imaging vessels and organ perfusion with high temporal resolution. Background signals are a major source for image artifacts and in turn restrict the sensitivity of the method in practice. While static background signals can be removed from the measured signal...

Magnetic Particle Imaging (MPI) has been successfully used to visualize the distribution of superparamagnetic nanoparticles within 3D volumes with high sensitivity in real time. Since the magnetic field topology of MPI scanners is well suited for applying magnetic forces on particles and micron-sized ferromagnetic devices, MPI has been recently use...

Magnetic particle imaging (MPI) data is commonly reconstructed using a system matrix acquired in a time-consuming calibration measurement. The calibration approach has the important advantage over model-based reconstruction that it takes the complex particle physics as well as system imperfections into account. This benefit comes for the cost that...

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 image...

The increased availability of X-ray image archives (e.g. the ChestX-ray14 dataset from the NIH Clinical Center) has triggered a growing interest in deep learning techniques. To provide better insight into the different approaches, and their applications to chest X-ray classification, we investigate a powerful network architecture in detail: the Res...