| 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 | 301 | 2018 |
| nnu-net: Self-adapting framework for u-net-based medical image segmentation F Isensee, J Petersen, A Klein, D Zimmerer, PF Jaeger, S Kohl, ... arXiv preprint arXiv:1809.10486, 2018 | 169 | 2018 |
| 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, KH Maier-Hein International workshop on statistical atlases and computational models of …, 2017 | 122 | 2017 |
| nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation F Isensee, PF Jaeger, SAA Kohl, J Petersen, KH Maier-Hein Nature Methods, 1-9, 2020 | 114* | 2020 |
| 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, ... Machine Learning for Health Workshop, 171-183, 2020 | 49 | 2020 |
| 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 | 44 | 2018 |
| Deep probabilistic modeling of glioma growth J Petersen, PF Jäger, F Isensee, SAA Kohl, U Neuberger, W Wick, ... International Conference on Medical Image Computing and Computer-Assisted …, 2019 | 9 | 2019 |
| Revealing hidden potentials of the q-space signal in breast cancer PF Jäger, S Bickelhaupt, FB Laun, W Lederer, D Heidi, TA Kuder, ... International Conference on Medical Image Computing and Computer-Assisted …, 2017 | 9 | 2017 |
| Studying Robustness of Semantic Segmentation under Domain Shift in cardiac MRI PM Full, F Isensee, PF Jäger, K Maier-Hein arXiv preprint arXiv:2011.07592, 2020 | 1 | 2020 |
| Reg R-CNN: lesion detection and grading under noisy labels GN Ramien, PF Jaeger, SAA Kohl, KH Maier-Hein Uncertainty for Safe Utilization of Machine Learning in Medical Imaging and …, 2019 | 1 | 2019 |
| nnU-Net for Brain Tumor Segmentation F Isensee, PF Jaeger, PM Full, P Vollmuth, KH Maier-Hein arXiv preprint arXiv:2011.00848, 2020 | | 2020 |
| Domain Adaptation for Deviating Acquisition Protocols in CNN-Based Lesion Classification on Diffusion-Weighted MR Images J Kamphenkel, PF Jäger, S Bickelhaupt, FB Laun, W Lederer, H Daniel, ... Image Analysis for Moving Organ, Breast, and Thoracic Images, 73-80, 2018 | | 2018 |
| Advanced Deep Learning Methods P Jäger, F Isensee, J Petersen, D Zimmerer, J Wasserthal, KH Maier-Hein Bildverarbeitung für die Medizin 2018, 6-6, 2018 | | 2018 |
| Retina U-Net for Aneurysm Detection in MR Images M Baumgartner, PF Jaeger, F Isensee, KH Maier-Hein | | |
| DKFZ-GE F Isensee, PF Jäger, SAA Kohl, J Petersen, KH Maier-Hein | | |
Klaus H. Maier-Hein (né Fritzsche)Professor, Division of Medical Image Computing, German Cancer Research Center在 dkfz.de 的电子邮件经过验证
