Biography

Dr. Giulio Dagnino is Research Associate in the Hamlyn Centre for Robotic Surgery at Imperial College London, UK. He is currently working on real-time control and navigation for an image-guided MRI-safe robotic platform for endovascular interventions. Dr. Dagnino’s interests and expertise are in robotics and computer assistance for medical applications. He aims to develop novel technologies to improve the current medical procedures, including enhanced treatment and diagnosis. The overall objective is providing as much information and support to the surgical team to produce better outcomes, and improve the quality of life of patients. Dr. Dagnino received his BSc and MSc in Biomedical Engineering at the University of Genoa, Italy. He graduated with a PhD in Medical Robotics from the Italian Institute of Technology in 2013, with a dissertation on new technologies for robot-assisted laser microsurgery. This work involved the incorporation of image-guided surgery, vision-based closed loop system control, and user interface design and evaluation. Dr. Dagnino joined the Bristol Robotics Laboratory, Bristol, UK in 2013 as a Postdoctoral Research Fellow working on robot-assisted fracture surgery. His research demonstrated the integration of robotic assistance and real-time image-guidance in minimally invasive orthopedic surgery.

Abstract

The goal of modern surgical technologies is providing as much information and support to the surgical team, to produce better outcomes and improve the quality of life of patients. Integrating robotics, medical imaging and sensing in a real-time surgical platform, can have a potentially tremendous impact on the surgical outcome. However, although robotics assistance is now widely used in the operating room, intra-operative medical imaging and sensing are currently limited in quality due to sub-optimal acquisition methods and limited integration with the robotic devices. As a result, while many robotic platforms for image-guided interventions have been proposed, few have become a clinical reality. This talk will describe advances in the integration of robotics, medical imaging, and sensing to realize original, clinically usable, image-guided robotic platforms. The overarching hypothesis of this research is that such integration will produce safer and clinically usable surgical robots that will increase the quality and cost effectiveness of surgical procedures. To realize this research vision, new theory, computing, control algorithms, and real-time implementations are needed to underpin the integration of robotic systems, medical imaging and sensing within dynamic environments. In this talk, the author will use image-guided robotic surgical platforms from his work as an example to propose broader research directions that will enable us to address these challenges.