2024
Journals
Henschel, Lenonie; Kügler, David; Zöllei, Lilla*; Reuter, Martin* (2024): VINNA for neonates: Orientation independence through latent augmentations. In Imaging Neuroscience 2, p. 1-16. DOI: 10.1162/imag_a_00180.
*Equal Contribution
Ewert, Christian*; Kügler, David*; Reuter, Martin (2024): Geometric deep learning for diffusion MRI signal reconstruction with continuous samplings (DISCUS). In Imaging Neuroscience 2, p. 1-18. DOI: 10.1162/imag_a_00121.
*Equal Contribution
Ferreira, Mónica; Schaprian, Tamara; Kügler, David; Reuter, Martin; … Faber, Jennifer (2024): Cerebellar Volumetry in Ataxias: Relation to Ataxia Severity and Duration. In Cerebellum. DOI: 10.1007/s12311-024-01659-0.
2023
Journals
Pollak, Clemens; Kügler, David; Breteler, Monique M.B.; Reuter, Martin (2023): Quantifying MR head motion in the Rhineland Study – A robust method for population cohorts. In NeuroImage 275, p. 120176. DOI: 10.1016/j.neuroimage.2023.120176.
Estrada, Santiago; Kügler, David; Bahrami, Emad; Xu, Peng; Mousa, Dilshad; Breteler, Monique M.B.; Aziz, N. Ahmad; Reuter, Martin (2023): FastSurfer-HypVINN: Automated subsegmentation of the hypothalamus and adjacent structures on high-resolutional brain MRI. In Imaging Neuroscience 1, p. 1-32. DOI: 10.1162/imag_a_00034.
Conferences
Pollak, Clemens*; Kügler, David*; Reuter, Martin (2023): Estimating Head Motion from MRI. In International Symposium on Biomedical Imaging (ISBI), p. XX. DOI: XX. Avaliable online at https://arxiv.org/pdf/2302.1449.
*Equal Contribution
2022
Journals
Faber, Jenny*; Kügler, David*; Bahrami, Emad*; Heinz, Lea-Sophie; Timmann, Dagmar; Ernst, Thomas M.; Deike-Hofmann, Katerina; Klockgether, Thoma; van de Warrenburg, Bart; van Gaalen, Judith; Reetz, Kathrin; Romanzetti, Sandro; Oz, Gulin; Joers, James M.; Diedrichsen, Jorn; ESMI MR Study Group; Reuter, Martin (2022): CerebNet: A fast and reliable deep-learning pipeline for detailed cerebellum sub-segmentation. In NeuroImage 251, p. 119703. DOI: 10.1016/j.neuroimage.2022.119703.
*Equal Contribution
Henschel, Leonie*; Kügler, David*; Reuter, Martin (2022): FastSurferVINN: Building resolution-independence into deep learning segmentation methods-A solution for HighRes brain MRI. In NeuroImage 251, p. 118933. DOI: 10.1016/j.neuroimage.2022.118933.
*Equal Contribution
Conferences
Roy, Saikat*; Kügler, David*; Reuter, Martin (2022): Are 2.5D approaches superior to 3D deep networks in whole brain segmentation? In Medical Imaging with Deep Learning. Zürich, Switzerland, 6.7.-8.7.2022. MIDL. Available online at https://openreview.net/forum?id=Ob62JPB_CDF.
*Equal Contribution
Henschel, Leonie; Kügler, David; Andrews, Derek S.; Nordahl, Christine W.; Reuter, Martin (2022): Identifying and Combating Bias in Segmentation Networks by leveraging multiple resolutions. In Medical Image Computing and Computer Assisted-Intervention. MICCAI. Available online at https://arxiv.org/pdf/2206.14919.
2020
Journals
Kügler, David; Sehring, Jannik; Stefanov, Andrei; Stenin, Igor; Kristin, Julia; Klenzner, Thomas et al. (2020): i3PosNet: Instrument Pose Estimation from X-Ray in temporal bone surgery. In International journal of computer assisted radiology and surgery 15 (7), 1137–1145. Available online at https://link.springer.com/article/10.1007/s11548-020-02157-4.
Krumb, Henry; Hofmann, Sofie; Kügler, David; Ghazy, Ahmed; Dorweiler, Bernhard; Bredemann, Judith et al. (2020): Leveraging spatial uncertainty for online error compensation in EMT. In International journal of computer assisted radiology and surgery 15 (6), pp. 1043–1051. doi: 10.1007/s11548-020-02189-w. Available online at https://link.springer.com/article/10.1007%2Fs11548-020-02189-w
Conferences
Kügler, David*; Uecker, Marc*; Kuijper, Arjan; Mukhopadhyay, Anirban:
AutoSNAP: Automatically Learning Neural Architectures for Instrument Pose Estimation. In : MICCAI 2020. Available online at http://arxiv.org/pdf/2006.14858.
*Equal contribution
Workshops
Ewert, Christian*, Kügler, David*; Yendiki, Anastasia; Reuter, Martin: Learning Anatomical Segmentations for Tractography from Diffusion MRI. In cdmri’20 Workshop. Available online at http://arxiv.org/pdf/2009.04392.
*Equal contribution
2019
Journals
Kügler, David; Krumb, Henry; Bredemann, Judith; Stenin, Igor; Kristin, Julia; Klenzner, Thomas et al. (2019): High-Precision Evaluation of Electromagnetic Tracking. In International journal of computer assisted radiology and surgery. doi: 10.1007/s11548-019-01959-5
Others
Mukhopadhyay, Anirban; Kügler, David; Bucher, Andreas; Fellner, Dieter; Vogl, Thomas (2019): Putting Trust first in the Translation of AI for Healthcare.In ERCIM News (116), pp. 20–22. Available online at https://ercim-news.ercim.eu/en116/special/putting-trust-first-in-the-translation-of-ai-for-healthcare.
Kügler, David; Bucher, Andreas; Kleemann, Johannes; Distergoft, Alexander; Jabhe, Ali; Uecker, Marc et al. (2018): Physical World Attacks: An evaluation of robustness for Deep-Learning in Dermoscopy. Available online at https://openreview.net/pdf?id=Byl6W7WeeN.
2018
Workshops & Other
Kügler, David; Jastrzebski, Martin; Mukhopadhyay, Anirban (2018):
Instrument Pose Estimation using Registration for Otobasis Surgery.
In 8th International Workshop on Biomedical Image Registration, WBIR2018. doi: 10.1007/978-3-319-92258-4_10 .
Kügler, David; Distergoft, Alexander; Kuijper, Arjan; Mukhopadhyay, Anirban (2018): Exploring Adversarial Examples: Patterns of One-Pixel Attacks. In Understanding and Interpreting Machine Learning in Medical Image Computing Applications, vol. 11038. Cham: Springer, pp. 70–78. Available online at http://arxiv.org/pdf/1806.09410.
Kügler, David; Mukhopadhyay, Anirban (2018): How Bad is Good enough. Noisy annotations for instrument pose estimation. Available online at http://arxiv.org/pdf/1806.07836.