Tobias Kluth
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View article: Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging
Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Open
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 t…
View article: Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging
Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Open
View article: Data-driven approaches for electrical impedance tomography image segmentation from partial boundary data
Data-driven approaches for electrical impedance tomography image segmentation from partial boundary data Open
Electrical impedance tomography (EIT) plays a crucial role in non-invasive imaging, with both medical and industrial applications. In this paper, we present three data-driven reconstruction methods for EIT imaging. These three approaches w…
View article: Equilibrium Model with Anisotropy for Model-Based Reconstruction in Magnetic Particle Imaging
Equilibrium Model with Anisotropy for Model-Based Reconstruction in Magnetic Particle Imaging Open
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, t…
View article: Bayesian view on the training of invertible residual networks for solving linear inverse problems <sup>*</sup>
Bayesian view on the training of invertible residual networks for solving linear inverse problems <sup>*</sup> Open
Learning-based methods for inverse problems, adapting to the data’s inherent structure, have become ubiquitous in the last decade. Besides empirical investigations of their often remarkable performance, an increasing number of works addres…
View article: Equilibrium Model With Anisotropy for Model-Based Reconstruction in Magnetic Particle Imaging
Equilibrium Model With Anisotropy for Model-Based Reconstruction in Magnetic Particle Imaging Open
View article: Data-driven approaches for electrical impedance tomography image segmentation from partial boundary data
Data-driven approaches for electrical impedance tomography image segmentation from partial boundary data Open
Electrical impedance tomography (EIT) plays a crucial role in non-invasive imaging, with both medical and industrial applications. In this paper, we present three data-driven reconstruction methods for EIT imaging, that were submitted to t…
View article: Learning-Based Approaches for Reconstructions With Inexact Operators in nanoCT Applications
Learning-Based Approaches for Reconstructions With Inexact Operators in nanoCT Applications Open
Imaging problems such as the one in nanoCT require the solution of an inverse problem, where it is often taken for granted that the forward operator, i.e., the underlying physical model, is properly known. In the present work we address th…
View article: Invertible residual networks in the context of regularization theory for linear inverse problems
Invertible residual networks in the context of regularization theory for linear inverse problems Open
Learned inverse problem solvers exhibit remarkable performance in applications like image reconstruction tasks. These data-driven reconstruction methods often follow a two-step procedure. First, one trains the often neural network-based re…
View article: Simulated nanoCT Datasets
Simulated nanoCT Datasets Open
Simulated parallel-beam and fan-beam nano-CT datasets with per-angle random phantom shifts and rotations. The dataset generation is described in the paper Learning-based approaches for reconstructions with inexact operators in nanoCT appli…
View article: Simulated nanoCT Datasets
Simulated nanoCT Datasets Open
Simulated parallel-beam and fan-beam nano-CT datasets with per-angle random phantom shifts and rotations. The dataset generation is described in the paper Learning-based approaches for reconstructions with inexact operators in nanoCT appli…
View article: Learning-based approaches for reconstructions with inexact operators in nanoCT applications
Learning-based approaches for reconstructions with inexact operators in nanoCT applications Open
Imaging problems such as the one in nanoCT require the solution of an inverse problem, where it is often taken for granted that the forward operator, i.e., the underlying physical model, is properly known. In the present work we address th…
View article: Bayesian view on the training of invertible residual networks for solving linear inverse problems
Bayesian view on the training of invertible residual networks for solving linear inverse problems Open
Learning-based methods for inverse problems, adapting to the data's inherent structure, have become ubiquitous in the last decade. Besides empirical investigations of their often remarkable performance, an increasing number of works addres…
View article: Time-dependent parameter identification in a Fokker-Planck equation based magnetization model of large ensembles of nanoparticles
Time-dependent parameter identification in a Fokker-Planck equation based magnetization model of large ensembles of nanoparticles Open
In this article, we consider a model motivated by large ensembles of nanoparticles' magnetization dynamics using the Fokker-Planck equation and analyze the underlying parabolic PDE being defined on a smooth, compact manifold without bounda…
View article: Dynamic image reconstruction with motion priors in application to 3D magnetic particle imaging
Dynamic image reconstruction with motion priors in application to 3D magnetic particle imaging Open
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 als…
View article: Invertible residual networks in the context of regularization theory for linear inverse problems
Invertible residual networks in the context of regularization theory for linear inverse problems Open
Learned inverse problem solvers exhibit remarkable performance in applications like image reconstruction tasks. These data-driven reconstruction methods often follow a two-step scheme. First, one trains the often neural network-based recon…
View article: Estimating the Spatial Orientation of Immobilized Magnetic Nanoparticles with Parallel-Aligned Easy Axes
Estimating the Spatial Orientation of Immobilized Magnetic Nanoparticles with Parallel-Aligned Easy Axes Open
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 ensem…
View article: Modeling the magnetization dynamics for large ensembles of immobilized magnetic nanoparticles in multi-dimensional magnetic particle imaging
Modeling the magnetization dynamics for large ensembles of immobilized magnetic nanoparticles in multi-dimensional magnetic particle imaging Open
View article: MPIData: Easy Axis Orientation Estimation
MPIData: Easy Axis Orientation Estimation Open
This data repository contains magnetic particle imaging data. The files are stored in the MDF file format and the folder structure is organized as an MDF store. The data is used in this code example.
View article: MPIData: Easy Axis Orientation Estimation
MPIData: Easy Axis Orientation Estimation Open
This data repository contains magnetic particle imaging data. The files are stored in the MDF file format and the folder structure is organized as an MDF store. The data is used in this code example.
View article: A simulation framework for particle magnetization dynamics of large ensembles of single domain particles: Numerical treatment of Brown/Néel dynamics and parameter identification problems in magnetic particle imaging
A simulation framework for particle magnetization dynamics of large ensembles of single domain particles: Numerical treatment of Brown/Néel dynamics and parameter identification problems in magnetic particle imaging Open
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 rotati…
View article: Recent Developments on System Function/Matrix Representation, Hybrid Simulation Techniques, and Magnetic Actuation
Recent Developments on System Function/Matrix Representation, Hybrid Simulation Techniques, and Magnetic Actuation Open
The first issue of the sixth volume of the International Journal on Magnetic Particle Imaging presents four papers focusing on different aspects of the image reconstruction problem in magnetic particle imaging (MPI) and developments in mag…
View article: Deep image prior for 3D magnetic particle imaging: A quantitative\n comparison of regularization techniques on Open MPI dataset
Deep image prior for 3D magnetic particle imaging: A quantitative\n comparison of regularization techniques on Open MPI dataset Open
Magnetic particle imaging (MPI) is an imaging modality exploiting the\nnonlinear magnetization behavior of (super-)paramagnetic nanoparticles to\nobtain a space- and often also time-dependent concentration of a tracer\nconsisting of these …
View article: Deep image prior for 3D magnetic particle imaging: A quantitative comparison of regularization techniques on Open MPI dataset
Deep image prior for 3D magnetic particle imaging: A quantitative comparison of regularization techniques on Open MPI dataset Open
Magnetic 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 nan…
View article: Software-based representation of selected benchmark hierarchies equipped with publically available data
Software-based representation of selected benchmark hierarchies equipped with publically available data Open
<p>Based on the multitude of industrial applications, benchmarks for model hierarchies will be created that will<br>\nform a basis for the interdisciplinary research and for the training programme. These will be equipped with&l…
View article: L1 data fitting for robust reconstruction in magnetic particle imaging: quantitative evaluation on Open MPI dataset
L1 data fitting for robust reconstruction in magnetic particle imaging: quantitative evaluation on Open MPI dataset Open
Magnetic 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 reconstructi…
View article: L1 data fitting for robust reconstruction in magnetic particle imaging: quantitative evaluation on Open MPI dataset
L1 data fitting for robust reconstruction in magnetic particle imaging: quantitative evaluation on Open MPI dataset Open
Magnetic 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 reconstructi…
View article: MNPDynamics: A computational toolbox for simulating magnetic moment behavior of ensembles of nanoparticles
MNPDynamics: A computational toolbox for simulating magnetic moment behavior of ensembles of nanoparticles Open
In the context of system function modeling for magnetic particle imaging, computing fast and accurate approximations to the time evolution of magnetic nanoparticles' (MNPs) mean magnetic moment is a problem of interest. In a software toolb…
View article: Estimating orientation using multi-contrast MPI
Estimating orientation using multi-contrast MPI Open
Magnetic 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 h…
View article: Towards accurate modeling of the multidimensional MPI physics
Towards accurate modeling of the multidimensional MPI physics Open
The MPI image reconstruction problem requires, particularly for 2D and 3D excitation patterns, a measured system matrix due to the lack of an accurate model that is capable of describing the nanoparticles’ magnetization behavior in the MPI…