Papers
25
Total Citations
583
H-Index
12
About
Mahdi Azizian is a pioneering researcher at the intersection of medical robotics, computer vision, and surgical automation, whose work has significantly advanced the capabilities of minimally invasive and robot-assisted surgery. His early contributions include developing autonomous image-guided robotic systems for catheter insertion, reducing radiation exposure risks for interventional cardiologists — a paper that has garnered 94 citations. Azizian's comprehensive two-part survey on visual servoing in medical robotics (totaling over 100 citations combined) remains a foundational reference for researchers navigating endoscopic, direct vision, and tomographic imaging modalities in surgical settings. His involvement in the 2017 Robotic Instrument Segmentation Challenge (57 citations) helped establish standardized benchmarks that accelerated progress in surgical computer vision. Further demonstrating his breadth, Azizian has explored augmented reality guidance for transoral robotic surgery and contributed to understanding the da Vinci Surgical System's capabilities. His more recent deep learning work — including temporal surgical subtask segmentation and the daVinciNet framework for joint motion and state prediction — reflects a forward-looking focus on surgical automation and shared control, essential stepping stones toward fully autonomous robotic surgery.
Research Focus
Key Achievements
Top Papers
- 1Autonomous Image-Guided Robot-Assisted Active Catheter Insertion94 citations · 2008
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- 32017 Robotic Instrument Segmentation Challenge57 citations · 2019
- 4Augmented reality and cone beam CT guidance for transoral robotic surgery47 citations · 2015
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- 6Augmented reality for image guidance in transoral robotic surgery34 citations · 2019
- 7Image-guided techniques in renal and hepatic interventions30 citations · 2012
- 8The da Vinci Surgical System28 citations · 2019
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