| nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation F Isensee*, PF Jaeger*, SAA Kohl, J Petersen, ... Nature methods 18 (2), 203-211, 2021 | 4027 | 2021 |
| Deep learning techniques for automatic MRI cardiac multi-structures segmentation and diagnosis: is the problem solved? O Bernard, A Lalande, C Zotti, F Cervenansky, X Yang, PA Heng, I Cetin, ... IEEE transactions on medical imaging 37 (11), 2514-2525, 2018 | 1691 | 2018 |
| The liver tumor segmentation benchmark (lits) P Bilic, P Christ, HB Li, E Vorontsov, A Ben-Cohen, G Kaissis, A Szeskin, ... Medical Image Analysis 84, 102680, 2023 | 1168 | 2023 |
| nnu-net: Self-adapting framework for u-net-based medical image segmentation F Isensee, J Petersen, A Klein, D Zimmerer, PF Jaeger, S Kohl, ... MICCAI 2018, Medical Segmentation Decathlon Challenge Entry, 2018 | 969 | 2018 |
| Monai: An open-source framework for deep learning in healthcare MJ Cardoso, W Li, R Brown, N Ma, E Kerfoot, Y Wang, B Murrey, ... arXiv preprint arXiv:2211.02701, 2022 | 388 | 2022 |
| Automatic cardiac disease assessment on cine-MRI via time-series segmentation and domain specific features F Isensee*, PF Jaeger*, PM Full, I Wolf, S Engelhardt, ... International workshop on statistical atlases and computational models of …, 2017 | 355 | 2017 |
| nnU-Net for brain tumor segmentation F Isensee, PF Jäger, PM Full, P Vollmuth, KH Maier-Hein Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2021 | 346 | 2021 |
| Automated design of deep learning methods for biomedical image segmentation F Isensee, PF Jäger, SAA Kohl, J Petersen, KH Maier-Hein arXiv preprint arXiv:1904.08128, 2019 | 302 | 2019 |
| Retina U-Net: Embarrassingly simple exploitation of segmentation supervision for medical object detection PF Jaeger, SAA Kohl, S Bickelhaupt, F Isensee, TA Kuder, HP Schlemmer, ... ML4H Workshop, Neurips, 171-183, 2020 | 243 | 2020 |
| nnu-net: Breaking the spell on successful medical image segmentation F Isensee, J Petersen, SAA Kohl, PF Jäger, KH Maier-Hein arXiv preprint arXiv:1904.08128 1 (1-8), 2, 2019 | 220 | 2019 |
| Metrics reloaded: Recommendations for image analysis validation L Maier-Hein, A Reinke, P Godau, MD Tizabi, F Buettner, E Christodoulou, ... Nature Methods, 1-18, 2024 | 216* | 2024 |
| Common limitations of image processing metrics: A picture story A Reinke, MD Tizabi, CH Sudre, M Eisenmann, T Rädsch, M Baumgartner, ... arXiv preprint arXiv:2104.05642, 2021 | 187 | 2021 |
| Radiomics based on adapted diffusion kurtosis imaging helps to clarify most mammographic findings suspicious for cancer S Bickelhaupt*, PF Jaeger*, FB Laun, W Lederer, H Daniel, TA Kuder, ... Radiology 287 (3), 761-770, 2018 | 103 | 2018 |
| 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 | 85 | 2023 |
| The cell tracking challenge: 10 years of objective benchmarking M Maška, V Ulman, P Delgado-Rodriguez, E Gómez-de-Mariscal, ... Nature Methods 20 (7), 1010-1020, 2023 | 82 | 2023 |
| nndetection: A self-configuring method for medical object detection M Baumgartner*, PF Jäger*, F Isensee, ... International Conference on Medical Image Computing and Computer-Assisted …, 2021 | 76 | 2021 |
| batchgenerators—a python framework for data augmentation F Isensee, P Jäger, J Wasserthal, D Zimmerer, J Petersen, S Kohl, ... Zenodo 3632567, 2020 | 62* | 2020 |
| Comparing methods of detecting and segmenting unruptured intracranial aneurysms on TOF-MRAS: the ADAM challenge KM Timmins, IC van der Schaaf, E Bennink, YM Ruigrok, X An, ... Neuroimage 238, 118216, 2021 | 60 | 2021 |
| Understanding metric-related pitfalls in image analysis validation A Reinke, MD Tizabi, M Baumgartner, M Eisenmann, D Heckmann-Nötzel, ... Nature methods 21 (2), 182-194, 2024 | 57 | 2024 |
| Studying robustness of semantic segmentation under domain shift in cardiac MRI PM Full, F Isensee, PF Jäger, K Maier-Hein Statistical Atlases and Computational Models of the Heart. M&Ms and EMIDEC …, 2021 | 56 | 2021 |
Klaus H. Maier-HeinProfessor, Medical Image Computing, German Cancer Research CenterVerified email at dkfz.de
