The use of robotic surgical systems - in conjunction with image guidance - is changing the world of surgery to less and less invasive procedures. As the field of robotic surgery evolves, the integration of pre- and per-operative medical imaging data becomes essential. This advanced visualization is necessary to provide a complete vision that includes anatomical, physiological, and functional information on the structures located in the field of intervention. Artificial intelligence (AI) and large data can facilitate the management and presentation of this crucial information by highlighting blood vessels, or tumor margins of tissues that may be difficult to discern with the naked eye or on a screen. AI in diagnostic medical imaging is already the precursor to the application of this technology in healthcare, with significant advances that take advantage of in-depth learning technologies. Image-guided surgery (IGS) - sometimes considered a global positioning system - as interventional radiology is gaining importance because it allows operators to perform minimally invasive surgical procedures in the inner part of solid organ where previously large resections had to be performed. For all pipe-shaped structures such as the digestive tract or bronchial tubes, robotic endoscopy will be needed to overcome the limits of standard therapeutic procedures by offering operating capacities close to those of rigid endoscopy. The need for imaging – pre- and per-operative - for endoscopic intervention is increasing to allow for more guidance in particular in the event of in-depth intervention.
I am a radiologist, professor of medicine both in France and Canada. Much of my research focus on abdominal imaging, both diagnostic and interventional, with a special interest in the therapy of cancer. When I arrived at McGill in 2013, as Chair and Director of the Imaging Department, I created in collaboration with the teams of computer Sciences from McGill (Center for Intelligent Machine) a research laboratory focus on Artificial Intelligence. My research activities are at the interface between Oncology, Medical Imaging, and Computer Vision with the objective of developing new methods of tumor quantification by imaging, in order to select patients who are likely to respond to a specific treatment and to evaluate their response very early. I was recently recruited - through an international competition
- by the University and the IHU of Strasbourg to take over the position of CEO of the IHU.