| Surgical data science–from concepts toward clinical translation L Maier-Hein, M Eisenmann, D Sarikaya, K März, T Collins, A Malpani, ... Medical image analysis 76, 102306, 2022 | 257 | 2022 |
| Exploiting the potential of unlabeled endoscopic video data with self-supervised learning LMH Tobias Ross, David Zimmerer, Anant Vemuri, Fabian Isensee, Manuel ... International Journal of Computer Assisted Radiology and Surgery, 1-9, 2018 | 157* | 2018 |
| Comparative validation of multi-instance instrument segmentation in endoscopy: Results of the robust-mis 2019 challenge T Roß, A Reinke, PM Full, M Wagner, H Kenngott, M Apitz, H Hempe, ... Medical Image Analysis 70, 101920, 2021 | 114* | 2021 |
| Generating large labeled data sets for laparoscopic image processing tasks using unpaired image-to-image translation M Pfeiffer, I Funke, MR Robu, S Bodenstedt, L Strenger, S Engelhardt, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 100 | 2019 |
| Heidelberg colorectal data set for surgical data science in the sensor operating room L Maier-Hein, M Wagner, T Ross, A Reinke, S Bodenstedt, PM Full, ... Scientific data 8 (1), 101, 2021 | 88 | 2021 |
| Labelling instructions matter in biomedical image analysis T Rädsch, A Reinke, V Weru, MD Tizabi, N Schreck, AE Kavur, ... Nature Machine Intelligence 5 (3), 273-283, 2023 | 53 | 2023 |
| Large-scale medical image annotation with crowd-powered algorithms E Heim, T Roß, A Seitel, K März, B Stieltjes, M Eisenmann, J Lebert, ... Journal of Medical Imaging 5 (3), 034002-034002, 2018 | 53 | 2018 |
| batchgenerators—a python framework for data augmentation F Isensee, P Jäger, J Wasserthal, D Zimmerer, J Petersen, S Kohl, ... Version 0.19 6, 2020 | 49 | 2020 |
| MOOD 2020: A public Benchmark for Out-of-Distribution Detection and Localization on medical Images D Zimmerer, PM Full, F Isensee, P Jäger, T Adler, J Petersen, G Köhler, ... IEEE Transactions on Medical Imaging 41 (10), 2728-2738, 2022 | 44 | 2022 |
| Crowd-algorithm collaboration for large-scale endoscopic image annotation with confidence L Maier-Hein, T Ross, J Gröhl, B Glocker, S Bodenstedt, C Stock, E Heim, ... Medical Image Computing and Computer-Assisted Intervention–MICCAI 2016: 19th …, 2016 | 44 | 2016 |
| Effectiveness and cost-effectiveness of four different strategies for SARS-CoV-2 surveillance in the general population (CoV-Surv Study): study protocol for a two … A Deckert, S Anders, M De Allegri, HT Nguyen, A Souares, S McMahon, ... Trials 22, 1-9, 2021 | 37 | 2021 |
| Crowdtruth validation: a new paradigm for validating algorithms that rely on image correspondences L Maier-Hein, D Kondermann, T Roß, S Mersmann, E Heim, S Bodenstedt, ... International journal of computer assisted radiology and surgery 10, 1201-1212, 2015 | 35 | 2015 |
| Beyond rankings: Learning (more) from algorithm validation T Roß, P Bruno, A Reinke, M Wiesenfarth, L Koeppel, PM Full, ... Medical Image Analysis 86, 102765, 2023 | 20* | 2023 |
| Clickstream analysis for crowd-based object segmentation with confidence E Heim, A Seitel, F Isensee, J Andrulis, C Stock, T Ross, L Maier-Hein IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017 | 18 | 2017 |
| batchgenerators-a python framework for data augmentation (2020) F Isensee, P Jäger, J Wasserthal, D Zimmerer, J Petersen, S Kohl, ... DOI: https://doi. org/10.5281/zenodo 3632567, 2020 | 15 | 2020 |
| Medical Outof-Distribution Analysis Challenge 2021 D Zimmerer, J Petersen, G Köhler, P Jäger, P Full, T Roß, T Adler, ... URL: https://doi. org/10.5281/zenodo 4573948, 2021 | 12 | 2021 |
| Medical out-of-distribution analysis challenge D Zimmerer, J Petersen, G Köhler, P Jäger, P Full, T Roß, T Adler, ... Zenodo, 2020 | 12 | 2020 |
| Heidelberg colorectal data set for surgical data science in the sensor operating room. Sci Data 8: 101 L Maier-Hein, M Wagner, T Ross, A Reinke, S Bodenstedt, PM Full, ... | 8 | 2021 |
| Medical out-of-distribution analysis challenge, Mar. 2020 D Zimmerer, J Petersen, G Köhler, P Jäger, P Full, T Roß, T Adler, ... URL https://doi. org/10.5281/zenodo 3784230, 0 | 7 | |
| How to create the largest in-vivo endoscopic dataset S Bittel, V Roethlingshoefer, H Kenngott, M Wagner, S Bodenstedt, ... Intravascular Imaging and Computer Assisted Stenting, and Large-Scale …, 2017 | 5 | 2017 |
