Mednext: transformer-driven scaling of convnets for medical image segmentation S Roy, G Koehler, C Ulrich, M Baumgartner, J Petersen, F Isensee, ... International Conference on Medical Image Computing and Computer-Assisted …, 2023 | 42 | 2023 |
How adsorbates alter the metallic behavior of quasi-1D electron systems of the Si (5 5 3)-Au surface M Tzschoppe, C Huck, F Hötzel, B Günther, Z Mamiyev, A Butkevich, ... Journal of Physics: Condensed Matter 31 (19), 195001, 2019 | 19 | 2019 |
Extending nnU-Net is all you need F Isensee, C Ulrich, T Wald, KH Maier-Hein BVM Workshop, 12-17, 2023 | 16 | 2023 |
Multitalent: A multi-dataset approach to medical image segmentation C Ulrich, F Isensee, T Wald, M Zenk, M Baumgartner, KH Maier-Hein International Conference on Medical Image Computing and Computer-Assisted …, 2023 | 15 | 2023 |
End-to-end deep learning CT image reconstruction for metal artifact reduction DF Bauer, C Ulrich, T Russ, AK Golla, LR Schad, FG Zöllner Applied Sciences 12 (1), 404, 2021 | 10 | 2021 |
Enhanced diagnostic fidelity in pathology whole slide image compression via deep learning M Fischer, P Neher, P Schüffler, S Xiao, SD Almeida, C Ulrich, ... International Workshop on Machine Learning in Medical Imaging, 427-436, 2023 | 2 | 2023 |
Transformer Utilization in Medical Image Segmentation Networks S Roy, G Koehler, M Baumgartner, C Ulrich, J Petersen, F Isensee, ... arXiv preprint arXiv:2304.04225, 2023 | 2 | 2023 |
Deposition-Dependent Morphology and Infrared Vibrational Spectra of Brominated Tetraazaperopyrene Layers M Tzschoppe, C Huck, B Günther, M Matthiesen, C Ulrich, JN Rose, ... The Journal of Physical Chemistry C 124 (1), 769-779, 2019 | 2 | 2019 |
Segrap2023: A benchmark of organs-at-risk and gross tumor volume segmentation for radiotherapy planning of nasopharyngeal carcinoma X Luo, J Fu, Y Zhong, S Liu, B Han, M Astaraki, S Bendazzoli, ... arXiv preprint arXiv:2312.09576, 2023 | 1 | 2023 |
Interface properties and dopability of an organic semiconductor: TAPP-Br variable as molecule but inert in the condensed phase M Tzschoppe, C Huck, A Butkevich, B Günther, C Ulrich, JN Rose, ... Journal of Materials Chemistry C 8 (29), 9898-9908, 2020 | 1 | 2020 |
Mitigating False Predictions In Unreasonable Body Regions C Ulrich, C Knobloch, JC Holzschuh, T Wald, MR Rokuss, M Zenk, ... arXiv preprint arXiv:2404.15718, 2024 | | 2024 |
nnU-Net Revisited: A Call for Rigorous Validation in 3D Medical Image Segmentation F Isensee, T Wald, C Ulrich, M Baumgartner, S Roy, K Maier-Hein, ... arXiv preprint arXiv:2404.09556, 2024 | | 2024 |
Skeleton Recall Loss for Connectivity Conserving and Resource Efficient Segmentation of Thin Tubular Structures Y Kirchhoff, MR Rokuss, S Roy, B Kovacs, C Ulrich, T Wald, M Zenk, ... arXiv preprint arXiv:2404.03010, 2024 | | 2024 |
3D Medical Image Segmentation with Transformer-based Scaling of ConvNets: MedNeXt S Roy, G Koehler, M Baumgartner, C Ulrich, F Isensee, PF Jaeger, ... BVM Workshop, 79-79, 2024 | | 2024 |
Multi-dataset Approach to Medical Image Segmentation: MultiTalent C Ulrich, F Isensee, T Wald, M Zenk, M Baumgartner, KH Maier-Hein BVM Workshop, 78-78, 2024 | | 2024 |
From Generalist to Specialist: Incorporating Domain-Knowledge into Flamingo for Chest X-Ray Report Generation R Stock, S Denner, Y Kirchhoff, C Ulrich, MR Rokuss, S Roy, N Disch, ... Medical Imaging with Deep Learning, 2024 | | 2024 |
RecycleNet: Latent Feature Recycling Leads to Iterative Decision Refinement G Koehler, T Wald, C Ulrich, D Zimmerer, PF Jaeger, JKH Franke, S Kohl, ... Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2024 | | 2024 |
Lost in Transformation: Current roadblocks for Transformers in 3D medical image segmentation S Roy, T Wald, M Baumgartner, C Ulrich, G Koehler, D Zimmerer, ... | | 2023 |
Exploring new ways: Enforcing representational dissimilarity to learn new features and reduce error consistency T Wald, C Ulrich, F Isensee, D Zimmerer, G Koehler, M Baumgartner, ... arXiv preprint arXiv:2307.02516, 2023 | | 2023 |
Combining Anomaly Detection and Supervised Learning for Medical Image Segmentation J Holzschuh, D Zimmerer, C Ulrich, M Baumgartner, G Koehler, ... Medical Imaging with Deep Learning, short paper track, 2023 | | 2023 |