Machine learning for surgical phase recognition: a systematic review CR Garrow, KF Kowalewski, L Li, M Wagner, MW Schmidt, S Engelhardt, ... Annals of surgery 273 (4), 684-693, 2021 | 214 | 2021 |
2017 robotic instrument segmentation challenge M Allan, A Shvets, T Kurmann, Z Zhang, R Duggal, YH Su, N Rieke, ... arXiv preprint arXiv:1902.06426, 2019 | 176 | 2019 |
Exploiting the potential of unlabeled endoscopic video data with self-supervised learning T Ross, D Zimmerer, A Vemuri, F Isensee, M Wiesenfarth, S Bodenstedt, ... International journal of computer assisted radiology and surgery 13, 925-933, 2018 | 154 | 2018 |
Comparative validation of single-shot optical techniques for laparoscopic 3-D surface reconstruction L Maier-Hein, A Groch, A Bartoli, S Bodenstedt, G Boissonnat, PL Chang, ... IEEE transactions on medical imaging 33 (10), 1913-1930, 2014 | 130 | 2014 |
Can masses of non-experts train highly accurate image classifiers? A crowdsourcing approach to instrument segmentation in laparoscopic images L Maier-Hein, S Mersmann, D Kondermann, S Bodenstedt, A Sanchez, ... Medical Image Computing and Computer-Assisted Intervention–MICCAI 2014: 17th …, 2014 | 108 | 2014 |
Physics‐based shape matching for intraoperative image guidance S Suwelack, S Röhl, S Bodenstedt, D Reichard, R Dillmann, T dos Santos, ... Medical physics 41 (11), 111901, 2014 | 99 | 2014 |
Using 3D convolutional neural networks to learn spatiotemporal features for automatic surgical gesture recognition in video I Funke, S Bodenstedt, F Oehme, F von Bechtolsheim, J Weitz, S Speidel International conference on medical image computing and computer-assisted …, 2019 | 98 | 2019 |
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 | 98 | 2019 |
Dense GPU‐enhanced surface reconstruction from stereo endoscopic images for intraoperative registration S Röhl, S Bodenstedt, S Suwelack, H Kenngott, BP Müller‐Stich, ... Medical physics 39 (3), 1632-1645, 2012 | 93 | 2012 |
Context-aware augmented reality in laparoscopic surgery D Katić, AL Wekerle, J Görtler, P Spengler, S Bodenstedt, S Röhl, ... Computerized Medical Imaging and Graphics 37 (2), 174-182, 2013 | 90 | 2013 |
2018 robotic scene segmentation challenge M Allan, S Kondo, S Bodenstedt, S Leger, R Kadkhodamohammadi, ... arXiv preprint arXiv:2001.11190, 2020 | 86 | 2020 |
A system for context-aware intraoperative augmented reality in dental implant surgery D Katić, P Spengler, S Bodenstedt, G Castrillon-Oberndorfer, ... International journal of computer assisted radiology and surgery 10, 101-108, 2015 | 86 | 2015 |
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 | 83 | 2021 |
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 | 73 | 2021 |
Comparative evaluation of instrument segmentation and tracking methods in minimally invasive surgery S Bodenstedt, M Allan, A Agustinos, X Du, L Garcia-Peraza-Herrera, ... arXiv preprint arXiv:1805.02475, 2018 | 72 | 2018 |
Development and validation of a sensor-and expert model-based training system for laparoscopic surgery: the iSurgeon KF Kowalewski, JD Hendrie, MW Schmidt, CR Garrow, T Bruckner, ... Surgical Endoscopy 31, 2155-2165, 2017 | 70 | 2017 |
Generative adversarial networks for specular highlight removal in endoscopic images I Funke, S Bodenstedt, C Riediger, J Weitz, S Speidel Medical imaging 2018: Image-guided procedures, robotic interventions, and …, 2018 | 64 | 2018 |
Comparative validation of machine learning algorithms for surgical workflow and skill analysis with the heichole benchmark M Wagner, BP Müller-Stich, A Kisilenko, D Tran, P Heger, L Mündermann, ... Medical image analysis 86, 102770, 2023 | 62 | 2023 |
Active learning using deep Bayesian networks for surgical workflow analysis S Bodenstedt, D Rivoir, A Jenke, M Wagner, M Breucha, B Müller-Stich, ... International journal of computer assisted radiology and surgery 14, 1079-1087, 2019 | 61 | 2019 |
Artificial intelligence-assisted surgery: potential and challenges S Bodenstedt, M Wagner, BP Müller-Stich, J Weitz, S Speidel Visceral Medicine 36 (6), 450-455, 2020 | 55 | 2020 |