Speaker
Description
Professor Mauricio Reyes began his academic journey in 2003 when he was awarded a French-Chilean scholarship to conduct his PhD studies at INRIA, France. His research work focused on developing AI technologies to improve the workflow for cancer patients.
His PhD thesis resulted in the development of novel image reconstruction techniques for respiratory motion compensation during PET imaging. This research work significantly improved the assessment of treatment response in lung cancer patients, demonstrating the potential of medical image computing technologies applied to medicine.
Early in his postdoctoral years, Professor Reyes developed innovative high-throughput computational analysis methodologies for in-silico orthopaedic implant design. This research work was highlighted by the Swiss National Science Foundation as an example of front-end Swiss research. He was able to further translate this technology, changing the way orthopedic implants are designed nowadays using computational tools. In 2008, he co-founded Crisalix, a successful Swiss company offering AI-based technologies for simulation of reconstructive breast surgery.
His work in computational modeling continued towards the challenging aspects of modelling pathology. Through EU-funded projects, he started in 2010 to develop AI solutions for neuro-oncology, with a particular focus on automated brain tumor burden assessment. His seminal research work, led to be the recipient of the MICCAI Young Scientist Publication award in 2016.
His translational research efforts led to the first-of-its-kind FDA-approved AI technology for brain tumor patients, and a Boston-based startup with a subsidiary branch in Switzerland to further develop AI technologies. Throughout his career, Professor Reyes has raised over 11M EUR acquired funds, over 400 authored articles, with over 28000 citations, and a H-index of 65. His work has pioneered in the important aspects of robust AI, and explainable AI (XAI), in the field of medical image analysis."
Summary
In this talk I will cover the basics and advanced topics in AI-based image segmentation, sharing our experience translating the technology for clinical use, as well as new trends and challenges ahead.