| Sparsity reconstruction in electrical impedance tomography: an experimental evaluation M Gehre, T Kluth, A Lipponen, B Jin, A Seppänen, JP Kaipio, P Maass Journal of Computational and Applied Mathematics 236 (8), 2126-2136, 2012 | 109 | 2012 |
| Regularization by architecture: A deep prior approach for inverse problems S Dittmer, T Kluth, P Maass, D Otero Baguer Journal of Mathematical Imaging and Vision 62, 456-470, 2020 | 100 | 2020 |
| Mathematical models for magnetic particle imaging T Kluth Inverse Problems 34 (8), 083001, 2018 | 51 | 2018 |
| An evidential approach to SLAM, path planning, and active exploration J Clemens, T Reineking, T Kluth International Journal of Approximate Reasoning 73, 1-26, 2016 | 51 | 2016 |
| Towards accurate modeling of the multidimensional magnetic particle imaging physics T Kluth, P Szwargulski, T Knopp New journal of physics 21 (10), 103032, 2019 | 39 | 2019 |
| Enhanced reconstruction in magnetic particle imaging by whitening and randomized SVD approximation T Kluth, B Jin Physics in Medicine & Biology 64 (12), 125026, 2019 | 35 | 2019 |
| Enhanced reconstruction in magnetic particle imaging by whitening and randomized SVD approximation T Kluth, B Jin Physics in Medicine & Biology 64 (12), 125026, 2019 | 35 | 2019 |
| Sparse 3D reconstructions in electrical impedance tomography using real data M Gehre, T Kluth, C Sebu, P Maass Inverse Problems in Science and Engineering 22 (1), 31-44, 2014 | 32 | 2014 |
| Improved image reconstruction in magnetic particle imaging using structural a priori information C Bathke, T Kluth, C Brandt, P Maaß International Journal on Magnetic Particle Imaging IJMPI 3 (1), 2017 | 31 | 2017 |
| Deep image prior for 3D magnetic particle imaging: A quantitative comparison of regularization techniques on Open MPI dataset S Dittmer, T Kluth, MTR Henriksen, P Maass arXiv preprint arXiv:2007.01593, 2020 | 29 | 2020 |
| On the degree of ill-posedness of multi-dimensional magnetic particle imaging T Kluth, B Jin, G Li Inverse Problems 34 (9), 095006, 2018 | 26 | 2018 |
| Modeling the magnetization dynamics for large ensembles of immobilized magnetic nanoparticles in multi-dimensional magnetic particle imaging H Albers, T Knopp, M Möddel, M Boberg, T Kluth Journal of magnetism and magnetic materials 543, 168534, 2022 | 22 | 2022 |
| Model uncertainty in magnetic particle imaging: Nonlinear problem formulation and model-based sparse reconstruction T Kluth, P Maass International Journal on Magnetic Particle Imaging IJMPI 3 (2), 2017 | 22 | 2017 |
| Simulating magnetization dynamics of large ensembles of single domain nanoparticles: Numerical study of Brown/Néel dynamics and parameter identification problems in magnetic … H Albers, T Kluth, T Knopp Journal of magnetism and magnetic materials 541, 168508, 2022 | 18 | 2022 |
| β-SLAM: Simultaneous localization and grid mapping with beta distributions J Clemens, T Kluth, T Reineking Information Fusion 52, 62-75, 2019 | 13 | 2019 |
| A deep prior approach to magnetic particle imaging S Dittmer, T Kluth, DO Baguer, P Maass Machine Learning for Medical Image Reconstruction: Third International …, 2020 | 12 | 2020 |
| Joint super-resolution image reconstruction and parameter identification in imaging operator: analysis of bilinear operator equations, numerical solution, and application to … T Kluth, C Bathke, M Jiang, P Maass Inverse Problems 36 (12), 124006, 2020 | 8 | 2020 |
| L1 data fitting for robust reconstruction in magnetic particle imaging: quantitative evaluation on Open MPI dataset T Kluth, B Jin arXiv preprint arXiv:2001.06083, 2020 | 8 | 2020 |
| Numerosity as a topological invariant T Kluth, C Zetzsche Journal of vision 16 (3), 30-30, 2016 | 8 | 2016 |
| Affordance-based object recognition using interactions obtained from a utility maximization principle T Kluth, D Nakath, T Reineking, C Zetzsche, K Schill Computer Vision-ECCV 2014 Workshops: Zurich, Switzerland, September 6-7 and …, 2015 | 7 | 2015 |
