Andrei Stefanov

Papers

Total Citations

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About

Andrei Stefanov is a leading researcher in computer-assisted surgery, with a primary focus on advancing Minimally Invasive Surgery (MIS) through novel pose estimation techniques. His most cited work, "i3PosNet: Instrument Pose Estimation from X-Ray" (2018, 6 citations), addresses a critical challenge in MIS: accurately determining the position and orientation of surgical instruments without relying on conventional optical or electromagnetic tracking systems. Stefanov’s major contribution lies in developing a deep learning framework that estimates instrument pose directly from intraoperative X-ray images, bypassing the limitations of line-of-sight and electromagnetic interference that plague traditional trackers. This innovation promises to enhance surgical precision in delicate procedures where conventional tracking fails. His work has been recognized for its potential to improve real-time surgical guidance, and he continues to explore the intersection of computer vision and medical robotics. With a growing citation footprint, Stefanov is establishing himself as a key figure in the field of surgical technology, offering solutions that could transform how surgeons navigate complex anatomical environments.