| Deep learning computed tomography: Learning projection-domain weights from image domain in limited angle problems T Würfl, M Hoffmann, V Christlein, K Breininger, Y Huang, M Unberath, ... IEEE transactions on medical imaging 37 (6), 1454-1463, 2018 | 256 | 2018 |
| Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers Z Li, X Liu, N Drenkow, A Ding, FX Creighton, RH Taylor, M Unberath Proceedings of the IEEE/CVF international conference on computer vision …, 2021 | 253 | 2021 |
| Artificial intelligence to diagnose ischemic stroke and identify large vessel occlusions: a systematic review NM Murray, M Unberath, GD Hager, FK Hui Journal of neurointerventional surgery 12 (2), 156-164, 2020 | 240 | 2020 |
| Neuralangelo: High-fidelity neural surface reconstruction Z Li, T Müller, A Evans, RH Taylor, M Unberath, MY Liu, CH Lin Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 181 | 2023 |
| Dense depth estimation in monocular endoscopy with self-supervised learning methods X Liu, A Sinha, M Ishii, GD Hager, A Reiter, RH Taylor, M Unberath IEEE transactions on medical imaging 39 (5), 1438-1447, 2019 | 130 | 2019 |
| DeepDRR - A Catalyst for Machine Learning in Fluoroscopy-guided Procedures M Unberath*, JN Zaech*, SC Lee, B Bier, J Fotouhi, M Armand, N Navab International Conference on Medical Image Computing and Computer-Assisted …, 2018 | 123 | 2018 |
| X-ray-transform Invariant Anatomical Landmark Detection for Pelvic Trauma Surgery B Bier*, M Unberath*, JN Zaech, J Fotouhi, M Armand, G Osgood, ... International Conference on Medical Image Computing and Computer Assisted …, 2018 | 116 | 2018 |
| A county-level dataset for informing the United States' response to COVID-19 BD Killeen, JY Wu, K Shah, A Zapaishchykova, P Nikutta, A Tamhane, ... arXiv preprint arXiv:2004.00756, 2020 | 115 | 2020 |
| Cai4cai: the rise of contextual artificial intelligence in computer-assisted interventions T Vercauteren, M Unberath, N Padoy, N Navab Proceedings of the IEEE 108 (1), 198-214, 2019 | 111 | 2019 |
| Explainable medical imaging AI needs human-centered design: guidelines and evidence from a systematic review H Chen, C Gomez, CM Huang, M Unberath npj Digital Medicine 5 (156), 2022 | 88 | 2022 |
| Marker‐free motion correction in weight‐bearing cone‐beam CT of the knee joint M Berger, K Müller, A Aichert, M Unberath, J Thies, JH Choi, R Fahrig, ... Medical physics 43 (3), 1235-1248, 2016 | 78 | 2016 |
| A systematic review of robustness in deep learning for computer vision: Mind the gap? N Drenkow, N Sani, I Shpitser, M Unberath arXiv preprint arXiv:2112.00639, 2021 | 76 | 2021 |
| On-the-fly augmented reality for orthopedic surgery using a multimodal fiducial S Andress*, A Johnson*, M Unberath*, AF Winkler*, K Yu, J Fotouhi, ... Journal of Medical Imaging 5 (2), 021209, 2018 | 76 | 2018 |
| 2018 robotic scene segmentation challenge M Allan, S Kondo, S Bodenstedt, S Leger, R Kadkhodamohammadi, ... arXiv preprint arXiv:2001.11190, 2020 | 74 | 2020 |
| Image guided percutaneous spine procedures using an optical see-through head mounted display: proof of concept and rationale G Deib, A Johnson, M Unberath, K Yu, S Andress, L Qian, G Osgood, ... Journal of neurointerventional surgery 10 (12), 1187-1191, 2018 | 70 | 2018 |
| Plan in 2-D, execute in 3-D: an augmented reality solution for cup placement in total hip arthroplasty J Fotouhi, CP Alexander, M Unberath, G Taylor, SC Lee, B Fuerst, ... Journal of Medical Imaging 5 (2), 021205-021205, 2018 | 60 | 2018 |
| E-dssr: efficient dynamic surgical scene reconstruction with transformer-based stereoscopic depth perception Y Long, Z Li, CH Yee, CF Ng, RH Taylor, M Unberath, Q Dou Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021 | 59 | 2021 |
| Self-supervised learning for dense depth estimation in monocular endoscopy X Liu, A Sinha, M Unberath, M Ishii, GD Hager, RH Taylor, A Reiter OR 2.0 Context-Aware Operating Theaters, Computer Assisted Robotic Endoscopy …, 2018 | 57 | 2018 |
| The impact of machine learning on 2d/3d registration for image-guided interventions: A systematic review and perspective M Unberath, C Gao, Y Hu, M Judish, RH Taylor, M Armand, R Grupp Frontiers in Robotics and AI 8, 716007, 2021 | 54 | 2021 |
| Extremely dense point correspondences using a learned feature descriptor X Liu, Y Zheng, B Killeen, M Ishii, GD Hager, RH Taylor, M Unberath Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 53 | 2020 |
Andreas K. MaierUniversity of Erlangen-Nuremberg在 fau.de 的电子邮件经过验证
