Papers
24
Total Citations
876
H-Index
15
About
Martin Wagner is a pioneering researcher at the intersection of computer-assisted surgery, artificial intelligence, and surgical robotics. His work spans real-time image guidance, surgical workflow analysis, instrument segmentation, and autonomous robotic systems — collectively advancing the frontier of intelligent, context-aware surgical assistance. Wagner's early contributions established clinical foundations for intraoperative imaging, including a landmark 2013 study on CT-guided laparoscopic liver surgery (96 citations). He has since become a leading voice in AI-assisted surgery, authoring influential reviews on its potential and challenges (82 citations) and pioneering deep learning methods for semantic organ segmentation in both conventional and hyperspectral imaging (84 citations). His leadership of major benchmark challenges — including ROBUST-MIS 2019 (89 citations) and HeiChole (96 citations) — has shaped community-wide standards for evaluating surgical AI systems. Perhaps most strikingly, Wagner's group demonstrated the first self-learning autonomous camera-guiding robot for minimally invasive surgery and advanced sim-to-real reinforcement learning for deformable tissue manipulation (66 citations). With over 730 citations across his top works alone, his research is actively redefining how intelligent systems will support surgeons in the operating room of tomorrow.
Research Focus
Key Achievements
Top Papers
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- 5Artificial Intelligence-Assisted Surgery: Potential and Challenges82 citations · 2020
- 6Computer-assisted abdominal surgery: new technologies75 citations · 2015
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- 8A learning robot for cognitive camera control in minimally invasive surgery55 citations · 2021
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