Antonela Zanuttini

Papers

Total Citations

H-Index

About

Antonela Zanuttini is a rising star in the field of medical robotics, with a focused expertise in the intersection of artificial intelligence, robotic control, and cardiac ultrasound imaging. Her research primarily addresses the critical challenges of automating cardiac examinations, aiming to enhance both image quality and patient safety. Her most significant contribution is the development of an AI-powered robust interaction force control method for a Cardiac Ultrasound Robotic System (CURS), which employs dual control loops and AI-driven image feedback to ensure safe, high-quality scans. This work, published in 2024, has already garnered 10 citations, signaling its immediate impact. Building on this, her 2025 paper introduces a robust deep feature ultrasound image-based visual servoing (UIBVS) technique, featuring a novel convolutional neural network, UCF-Net, trained for automatic cardiac examination. With 5 citations to date, this work demonstrates her continued innovation in the field. Zanuttini’s research is paving the way for safer, more reliable, and fully automated robotic ultrasound systems, positioning her as a key contributor to the future of non-invasive cardiac diagnostics.