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 | 24* | 2020 |
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 | 20 | 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 | 13 | 2019 |
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 | 10 | 2022 |
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 | 8 | 2017 |
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 |
Are 2.5 D approaches superior to 3D deep networks in whole brain segmentation? S Roy, D Kügler, M Reuter | 5 | 2021 |
Physical Attacks in Dermoscopy: An Evaluation of Robustness for clinical Deep-Learning D Kügler, A Bucher, J Kleemann, A Distergoft, A Jabhe, M Uecker, ... | 5 | 2018 |
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 |
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 | 4 | 2020 |
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 | 2 | 2023 |
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 | 2 | 2020 |
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 |
Estimating Head Motion from MR-Images C Pollak, D Kügler, M Reuter arXiv preprint arXiv:2302.14490, 2023 | | 2023 |
Identifying and Combating Bias in Segmentation Networks by leveraging multiple resolutions L Henschel, D Kügler, DS Andrews, CW Nordahl, M Reuter Medical Image Computing and Computer Assisted Intervention–MICCAI 2022: 25th …, 2022 | | 2022 |
CerebNet: Deep learning cerebellar subsegmentation for fast and reliable atrophy quantification J Faber, D Kuegler, E Bahrami, L Heinz, D Timmann, T Ernst, ... MOVEMENT DISORDERS 37, S35-S36, 2022 | | 2022 |
Adversarial Attacks in der Erkennung von Pneumothoraxes aus Röntgenthoraxaufnahmen: Eine beachtenswerte Schwachstelle in der Translation Künstlicher Neuronaler Netzwerke in die … A Bucher, A Distergoft, D Kuegler, A Rajkarnikar, M Uecker, ... RöFo-Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden …, 2020 | | 2020 |
Eine praktische Verteidigungsmethode gegen digitale Bildmanipulationen bei der Erkennung von Pneumothoraxes aus Röntgenthoraxaufnahmen: Sicherung der Robustheit von klinischen … A Bucher, D Kuegler, A Distergoft, A Rajkarnikar, M Uecker, P Kujiper, ... RöFo-Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden …, 2020 | | 2020 |