Leonardo Tanzi
Papers
2
Total Citations
123
H-Index
2
About
Leonardo Tanzi is a leading researcher at the intersection of artificial intelligence and surgical robotics, with a primary focus on real-time deep learning and augmented reality (AR) for minimally invasive procedures. His major contributions lie in developing intelligent frameworks that enable automatic, intra-operative 3D model registration and semantic segmentation from endoscopic video feeds. Notably, his 2021 work on "Real-time deep learning semantic segmentation during intra-operative surgery for 3D augmented reality assistance" (86 citations) pioneered a two-step system for aligning patient-specific 3D virtual models during robot-assisted radical prostatectomy, significantly enhancing surgical precision. Building on this, his 2022 deep learning framework (37 citations) achieved real-time organ position and rotation inference, allowing seamless overlay of anatomical models onto live video—a critical step toward truly intelligent surgical navigation. With over 120 combined citations for these foundational works, Tanzi’s research is shaping the future of computer-assisted surgery, offering surgeons unprecedented visual guidance and paving the way for safer, more accurate robotic interventions.
Research Focus
Key Achievements
Top Papers
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