About the speaker
Marco Battaglini is a researcher in the Department of Medicine, Surgery and Neuroscience at the University of Siena and CEO of Siena Imaging. With a background as a physicist, he received his PhD from Siena, spending periods as a visiting researcher in Oxford and Montreal. His current research interests aim to translate the assessment of atrophy in the brains of neurological patients into clinical practice by evaluating pathological deviations of atrophy measures from the norm using AI methods. He has published more than 60 articles in peer-reviewed journals and developed new tools for extraction, segmentation and detection of new brain lesions.
Abstract
Recent years have seen a proliferation of commercial platforms designed to automatically assess structural damage in magnetic resonance imaging (MRI) of the brain of neurodegenerative patients. These platforms make extensive use of artificial intelligence (AI) methods to make the assessment of pathological structural deviations in the brain faster and more accurate. In this presentation, we will discuss the different areas where AI can be used in this context, highlighting SIENA Imaging approaches and results. In detail, we will discuss some AI applications that we have recently developed and are implementing in our platform. We will bring examples of Deep Learning (DL) tools for the segmentation of MRI structures (thalamus, hippocampus and brain volumes), and of the use of machine learning (ML) and DL networks for clinical activity prediction and patient classification. The last part of the talk will be devoted to examining the issues involved in implementing these solutions in a platform and the numerous benefits this implementation could bring. The cons will focus on explaining the technical and bureaucratic aspects. The pros will instead focus on the new avenues that AI methods could open up, and are already opening up, in the monitoring of neurological diseases.