Enrico Vezzetti
Papers
11
Total Citations
281
H-Index
7
About
Enrico Vezzetti is a leading researcher at the intersection of artificial intelligence, computer vision, and robotic surgery, with a primary focus on developing real-time augmented reality (AR) systems for urological procedures. His major contributions center on creating deep learning frameworks that enable automatic 3D model registration and semantic segmentation during robot-assisted laparoscopic surgery, allowing surgeons to overlay patient-specific anatomical models directly onto the surgical video stream. His most impactful work, "Real-time deep learning semantic segmentation during intra-operative surgery for 3D augmented reality assistance" (86 citations), demonstrates a practical system for improving precision in robot-assisted radical prostatectomy. Vezzetti has also pioneered the Bleeding Artificial Intelligence Detector (BLAIR) system, which uses convolutional neural networks to predict intraoperative bleeding during robotic surgery. His research on 3D models has shown tangible clinical benefits, including reduced positive surgical margins after prostatectomy. With several papers published between 2019 and 2023, Vezzetti’s work is rapidly gaining recognition for pushing the boundaries of autonomous surgical assistance, making complex procedures safer and more reproducible through intelligent, real-time visual guidance.
Research Focus
Key Achievements
Top Papers
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- 63D augmentation of the surgical video stream: Toward a modular approach19 citations · 2020
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- 8Enhancing Spatial Navigation in Robot-Assisted Surgery: An Application5 citations · 2019
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