Alessandro Daducci - Simona Schiavi - CMIC/WEISS joint seminar series

Alessandro Daducci, Simona Schiavi - University of Verona, Dpt of Computer Science

Title - COMMIT: a flexible framework for microstructure informed tractography

Abstract
Tractography is an invaluable tool in neuroscience as it allows researchers to study in vivo and noninvasively the neuronal architecture of the brain. Despite this unique opportunity, several studies have recently exposed its poor anatomical accuracy and showed, in particular, that the reconstructions are not truly quantitative and that the high incidence of false positives can potentially bias any analysis based on this technique. In this talk, I will present the Convex Optimization Modeling for Microstructure Informed Tractography (COMMIT) and show some possibilities that this framework offers for improving the quality of tractography reconstructions.

Short bio
Alessandro Daducci obtained his Ph.D. in 2010 from the Department of Neuroscience, Biomedicine, and Movement Sciences of the University of Verona, Italy. Then he spent 5 years as a post-doctoral fellow under the supervision of Prof. Jean-Philippe Thiran at the École Polytechnique Fédérale de Lausanne (EPFL), Switzerland, and 1 year under the supervision of Prof. Maxime Descoteaux at the University of Sherbrooke, Canada. In 2016 he joined the Department of Computer Science of the University of Verona as an Assistant Professor and he was promoted to Associate Professor in 2019. In the past 6 years, his research interests have been centered on the development of new methods for microstructure informed tractography to increase the anatomical accuracy of the reconstructions and provide more veridical estimates of brain connectivity.
Simona Schiavi is a Post-Doc at the Department of Computer Science of the University of Verona. She works with Alessandro Daducci on the development of a truly quantitative and biologically meaningful analyses of brain connectivity. Her research interests lie in modelling, numerical simulation and clinical application of Diffusion MRI, biomedical imaging, inverse problems, soft computing and clustering.