| 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 | 96 | 2018 |
| A Probabilistic U-Net for Segmentation of Ambiguous Images SAA Kohl, B Romera-Paredes, C Meyer, J De Fauw, JR Ledsam, ... Advances in Neural Information Processing Systems (NeurIPS), 2018 | 95 | 2018 |
| Adversarial Networks for Prostate Cancer Detection S Kohl, D Bonekamp, HP Schlemmer, K Yaqubi, M Hohenfellner, ... Machine Learning for Health workshop, NIPS 2017, 2017 | 79* | 2017 |
| Radiomic machine learning for characterization of prostate lesions with MRI: comparison to ADC values D Bonekamp, S Kohl, M Wiesenfarth, P Schelb, JP Radtke, M Götz, ... Radiology 289 (1), 128-137, 2018 | 43 | 2018 |
| 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 | 37* | 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 2019, 2018 | 32 | 2018 |
| Classification of cancer at prostate MRI: deep learning versus clinical PI-RADS assessment P Schelb, S Kohl, JP Radtke, M Wiesenfarth, P Kickingereder, ... Radiology 293 (3), 607-617, 2019 | 20 | 2019 |
| Context-encoding variational autoencoder for unsupervised anomaly detection D Zimmerer, SAA Kohl, J Petersen, F Isensee, KH Maier-Hein MIDL 2019, Conference Abstract, 2018 | 14 | 2018 |
| Shallow‐impurity‐related binding energy and linear optical absorption in ring‐shaped quantum dots and quantum‐well wires under applied electric field SAA Kohl, RL Restrepo, ME Mora‐Ramos, CA Duque Physica Status Solidi (b) 252 (4), 786-794, 2015 | 9 | 2015 |
| Deep Probabilistic Modeling of Glioma Growth J Petersen, PF Jäger, F Isensee, SAA Kohl, U Neuberger, W Wick, ... MICCAI 2019, 2019 | 3 | 2019 |
| Unsupervised Anomaly Localization using Variational Auto-Encoders D Zimmerer, F Isensee, J Petersen, S Kohl, K Maier-Hein MICCAI 2019, 2019 | 3 | 2019 |
| A Case for the Score: Identifying Image Anomalies using Variational Autoencoder Gradients D Zimmerer, J Petersen, SAA Kohl, KH Maier-Hein Medical Imaging meets NeurIPS workshop, NeurIPS 2018, 2018 | 3 | 2018 |
| Tutorial: Deep learning advancing the state-of-the-art in medical image analysis V Christlein, FC Ghesu, T Würfl, A Maier, F Isensee, P Neher, ... Bildverarbeitung für die Medizin 2017, 6-7, 2017 | 3 | 2017 |
| A Hierarchical Probabilistic U-Net for Modeling Multi-Scale Ambiguities SAA Kohl, B Romera-Paredes, KH Maier-Hein, DJ Rezende, SM Eslami, ... Medical Imaging meets NeurIPS Workshop, NeurIPS 2019, 2019 | 2 | 2019 |
| Computer-assisted intra-operative verification of surgical outcome for the treatment of syndesmotic injuries through contralateral side comparison S Thomas, F Isensee, S Kohl, M Privalov, N Beisemann, B Swartman, ... International Journal of Computer Assisted Radiology and Surgery 14 (12 …, 2019 | 1 | 2019 |
| Closing the Gap between Prostate Cancer and Deep Learning Detection Tools Response P Schelb, S Kohl, JP Radtke, M Wiesenfarth, P Kickingereder, ... RADIOLOGY 295 (3), E9-+, 2020 | | 2020 |
| Semantic Segmentation of Ambiguous Images SAA Kohl PhD Thesis, Karlsruhe Institute of Technology, 2020 | | 2020 |
| Reg R-CNN: Lesion Detection and Grading under Noisy Labels GN Ramien, PF Jaeger, SAA Kohl, KH Maier-Hein UNSURE Workshop, MICCAI 2019, 2019 | | 2019 |
| Radiomic Machine Learning: Is It Really a Useful Method for the Characterization of Prostate Cancer? Response D Bonekamp, S Kohl, M Wiesenfarth, P Schelb, JP Radtke, M Goetz, ... RADIOLOGY 291 (1), 270-270, 2019 | | 2019 |
| Bi-institutioneller Vergleich manueller mit automatisch durch ein Adversarial Neural Network erstellten Prostatasegmentationen D Bonekamp, T Penzkofer, S Kohl, A Baur, J Radtke, H Cash, M Götz, ... RöFo-Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden …, 2018 | | 2018 |
Klaus H. Maier-Hein (né Fritzsche)Professor, Division of Medical Image Computing, German Cancer Research CenterVerified email at dkfz.de
