Papers
29
Total Citations
816
H-Index
15
About
Christophe Doignon is a pioneering researcher at the intersection of computer vision, medical robotics, and surgical automation, whose work has fundamentally advanced the field of robot-assisted minimally invasive surgery. His research focuses on visual servoing, image segmentation, pose estimation, and robotic guidance systems, with a particular emphasis on making surgical procedures safer and more precise through intelligent automation. Doignon's most influential contribution — his 2003 paper on autonomous 3D positioning of surgical instruments using visual servoing, now cited over 209 times — established a foundational framework for enabling robots to track and reposition laparoscopic tools in real time without surgeon intervention. Building on this, he developed robust color-based segmentation techniques for identifying surgical instruments within the abdominal cavity, and explored automated suturing strategies for laparoscopic needle handling, both highly challenging problems in surgical robotics. His work extends beyond soft-tissue surgery; he also designed a patient-mounted robotic platform for CT-guided interventional radiology procedures, earning 74 citations, demonstrating versatility across clinical contexts. With contributions spanning endoscopic path following, cylinder pose estimation, and multi-object intra-operative tracking, Doignon has assembled a cohesive and impactful body of research that continues to shape how autonomous systems are developed for the operating room.
Research Focus
Key Achievements
Top Papers
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- 2A Patient-Mounted Robotic Platform for CT-Scan Guided Procedures74 citations · 2008
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- 4Stitching Planning in Laparoscopic Surgery: Towards Robot-assisted Suturing47 citations · 2009
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