| FastSurferVINN: Building resolution-independence into deep learning segmentation methods—A solution for HighRes brain MRI L Henschel, D Kügler, M Reuter NeuroImage 251, 118933, 2022 | 47 | 2022 |
| i3PosNet: instrument pose estimation from X-ray in temporal bone surgery. D Kügler, J Sehring, A Stefanov, I Stenin, J Kristin, T Klenzner, J Schipper, ... International Journal of Computer Assisted Radiology and Surgery 15 (7 …, 2020 | 40* | 2020 |
| CerebNet: A fast and reliable deep-learning pipeline for detailed cerebellum sub-segmentation J Faber, D Kügler, E Bahrami, LS Heinz, D Timmann, TM Ernst, ... NeuroImage 264, 119703, 2022 | 31 | 2022 |
| High-precision evaluation of electromagnetic tracking D Kügler, H Krumb, J Bredemann, I Stenin, J Kristin, T Klenzner, ... International journal of computer assisted radiology and surgery 14 (7 …, 2019 | 19 | 2019 |
| Are 2.5 D approaches superior to 3D deep networks in whole brain segmentation? S Roy, D Kügler, M Reuter | 12 | 2021 |
| Control methods for robot-based predictive compensation of respiratory motion H Arenbeck, L Wittschier, D Kügler, D Abel Biomedical Signal Processing and Control 34, 16-24, 2017 | 10 | 2017 |
| Quantifying MR head motion in the Rhineland Study–A robust method for population cohorts C Pollak, D Kügler, MMB Breteler, M Reuter NeuroImage 275, 120176, 2023 | 9 | 2023 |
| FastSurfer-HypVINN: Automated sub-segmentation of the hypothalamus and adjacent structures on high-resolutional brain MRI S Estrada, D Kügler, E Bahrami, P Xu, D Mousa, MMB Breteler, NA Aziz, ... Imaging Neuroscience 1, 1-32, 2023 | 8 | 2023 |
| Exploring Adversarial Examples: Patterns of One-Pixel Attacks D Kügler, A Distergoft, A Kuijper, A Mukhopadhyay Understanding and Interpreting Machine Learning in Medical Image Computing …, 2018 | 7 | 2018 |
| Physical Attacks in Dermoscopy: An Evaluation of Robustness for clinical Deep-Learning D Kügler, A Bucher, J Kleemann, A Distergoft, A Jabhe, M Uecker, ... | 6 | 2018 |
| Leveraging spatial uncertainty for online error compensation in emt H Krumb, S Hofmann, D Kügler, A Ghazy, B Dorweiler, J Bredemann, ... International Journal of Computer Assisted Radiology and Surgery 15, 1043-1051, 2020 | 5 | 2020 |
| Instrument Pose Estimation Using Registration for Otobasis Surgery D Kügler, MA Jastrzebski, A Mukhopadhyay International Workshop on Biomedical Image Registration, 105-114, 2018 | 5 | 2018 |
| AutoSNAP: Automatically Learning Neural Architectures for Instrument Pose Estimation D Kügler, M Uecker, A Kuijper, A Mukhopadhyay International Conference on Medical Image Computing and Computer-Assisted …, 2020 | 4 | 2020 |
| Geometric deep learning for diffusion MRI signal reconstruction with continuous samplings (DISCUS) C Ewert, D Kügler, R Stirnberg, A Koch, A Yendiki, M Reuter Imaging Neuroscience 2, 1-18, 2024 | 3 | 2024 |
| VINNA for neonates: Orientation independence through latent augmentations L Henschel, D Kügler, L Zöllei, M Reuter Imaging Neuroscience 2, 1-26, 2024 | 2 | 2024 |
| Cerebellar volumetry in ataxias: Relation to ataxia severity and duration M Ferreira, T Schaprian, D Kügler, M Reuter, K Deike-Hoffmann, ... The Cerebellum, 1-9, 2024 | 2 | 2024 |
| Estimating Head Motion from MR-Images C Pollak, D Kügler, M Reuter arXiv preprint arXiv:2302.14490, 2023 | 2 | 2023 |
| Learning Anatomical Segmentations for Tractography from Diffusion MRI C Ewert, D Kügler, A Yendiki, M Reuter Computational Diffusion MRI, 81-93, 2021 | 1 | 2021 |
| Putting Trust first in the Translation of AI for healthcare A Mukhopadhyay, D Kügler, A Bucher, D Fellner, T Vogl ERCIM news, 20-22, 2019 | 1 | 2019 |
| How Bad is Good enough: Noisy annotations for instrument pose estimation D Kügler, A Mukhopadhyay arXiv preprint arXiv:1806.07836, 2018 | 1 | 2018 |
Prof. Dr. Martin ReuterDirector AI in Medical Imaging DZNE Bonn Germany, Radiology & Neurology at Harvard Medical SchoolDirección de correo verificada de mgh.harvard.edu