| Impact of 18F-FET PET on Target Volume Definition and Tumor Progression of Recurrent High Grade Glioma Treated with Carbon-Ion Radiotherapy C Debus, M Waltenberger, R Floca, A Afshar-Oromieh, N Bougatf, ... Scientific reports 8 (1), 7201, 2018 | 43 | 2018 |
| MITK-ModelFit: A generic open-source framework for model fits and their exploration in medical imaging–design, implementation and application on the example of DCE-MRI C Debus, R Floca, M Ingrisch, I Kompan, K Maier-Hein, A Abdollahi, ... BMC bioinformatics 20, 1-18, 2019 | 35 | 2019 |
| A point kernel algorithm for microbeam radiation therapy C Debus, U Oelfke, S Bartzsch Physics in Medicine & Biology 62 (21), 8341, 2017 | 22 | 2017 |
| Deep-Learning-Based 3-D Surface Reconstruction—A Survey A Farshian, M Götz, G Cavallaro, C Debus, M Nießner, JA Benediktsson, ... Proceedings of the IEEE, 2023 | 21 | 2023 |
| Feasibility and robustness of dynamic 18F-FET PET based tracer kinetic models applied to patients with recurrent high-grade glioma prior to carbon ion irradiation C Debus, A Afshar-Oromieh, R Floca, M Ingrisch, M Knoll, J Debus, ... Scientific reports 8 (1), 14760, 2018 | 21 | 2018 |
| Reporting electricity consumption is essential for sustainable AI C Debus, M Piraud, A Streit, F Theis, M Götz Nature Machine Intelligence 5 (11), 1176-1178, 2023 | 17 | 2023 |
| HeAT–a distributed and GPU-accelerated tensor framework for data analytics M Götz, C Debus, D Coquelin, K Krajsek, C Comito, P Knechtges, ... 2020 IEEE International Conference on Big Data (Big Data), 276-287, 2020 | 17 | 2020 |
| Precise energy consumption measurements of heterogeneous artificial intelligence workloads R Caspart, S Ziegler, A Weyrauch, H Obermaier, S Raffeiner, ... International Conference on High Performance Computing, 108-121, 2022 | 15 | 2022 |
| Massively parallel genetic optimization through asynchronous propagation of populations O Taubert, M Weiel, D Coquelin, A Farshian, C Debus, A Schug, A Streit, ... International Conference on High Performance Computing, 106-124, 2023 | 13 | 2023 |
| Process Insights into Perovskite Thin‐Film Photovoltaics from Machine Learning with In Situ Luminescence Data F Laufer, S Ziegler, F Schackmar, EA Moreno Viteri, M Götz, C Debus, ... Solar RRL 7 (7), 2201114, 2023 | 13 | 2023 |
| Impact of fitting algorithms on errors of parameter estimates in dynamic contrast-enhanced MRI C Debus, R Floca, D Nörenberg, A Abdollahi, M Ingrisch Physics in Medicine & Biology 62 (24), 9322, 2017 | 12 | 2017 |
| Bolus arrival time estimation in dynamic contrast-enhanced magnetic resonance imaging of small animals based on spline models AL Bendinger, C Debus, C Glowa, CP Karger, J Peter, M Storath Physics in Medicine & Biology 64 (4), 045003, 2019 | 11 | 2019 |
| A community‐endorsed open‐source lexicon for contrast agent–based perfusion MRI: A consensus guidelines report from the ISMRM Open Science Initiative for Perfusion Imaging (OSIPI) BR Dickie, Z Ahmed, J Arvidsson, LC Bell, DL Buckley, C Debus, ... Magnetic resonance in medicine 91 (5), 1761-1773, 2024 | 9 | 2024 |
| Accelerating neural network training with distributed asynchronous and selective optimization (DASO) D Coquelin, C Debus, M Götz, F von der Lehr, J Kahn, M Siggel, A Streit Journal of Big Data 9 (1), 14, 2022 | 9 | 2022 |
| Impact of single dose photons and carbon ions on perfusion and vascular permeability: a dynamic contrast-enhanced MRI pilot study in the anaplastic rat prostate tumor R3327-AT1 AL Bendinger, L Seyler, M Saager, C Debus, P Peschke, D Komljenovic, ... Radiation Research 193 (1), 34-45, 2020 | 9 | 2020 |
| Discovering Process Dynamics for Scalable Perovskite Solar Cell Manufacturing with Explainable AI L Klein, S Ziegler, F Laufer, C Debus, M Götz, K Maier‐Hein, UW Paetzold, ... Advanced Materials 36 (7), 2307160, 2024 | 8 | 2024 |
| perun: Benchmarking Energy Consumption of High-Performance Computing Applications JP Gutiérrez Hermosillo Muriedas, K Flügel, C Debus, H Obermaier, ... European Conference on Parallel Processing, 17-31, 2023 | 8 | 2023 |
| Feed-forward optimization with delayed feedback for neural networks K Flügel, D Coquelin, M Weiel, C Debus, A Streit, M Götz arXiv preprint arXiv:2304.13372, 2023 | 8 | 2023 |
| High-performance data analytics of hybrid rocket fuel combustion data using different machine learning approaches C Debus, A Ruettgers, A Petrarolo, M Kobald, M Siggel AIAA Scitech 2020 Forum, 1161, 2020 | 8 | 2020 |
| RNA contact prediction by data efficient deep learning O Taubert, F von der Lehr, A Bazarova, C Faber, P Knechtges, M Weiel, ... Communications biology 6 (1), 913, 2023 | 4 | 2023 |
Markus GötzGroup leader, Karlsruhe Institute of Technology (KIT), Helmholtz AIDirección de correo verificada de kit.edu
