Thursday 17 Jan h.12:00 @ IDSIA (room announcement will follow). Doodle link: https://doodle.com/poll/uepiefttq752686w Title: Image driven systems immunology via semi-supervised machine learning and in-vivo microscopy Abstract: This talk describes the combination of machine learning with microscopy techniques for investigating the mechanisms of the immune system. After giving an overview about the applications of machine learning to in-vivo imaging, the capabilities of a graph-based, semi-supervised clustering algorithm will be presented. More in details, the immune system involves a complex network of cellular interactions. This network can be described as a system whose output can be either protective (i.e. from pathogens and tumors) or pathogenic (i.e. leading to autoimmune diseases). In-vivo video microscopy (IVM) is a recently developed method to investigate the behavior of the immune system in living animals. IVM acquires 4D videos capturing the migration of cells which correlates to their spatiotemporal interaction patterns. However, automatic classical automatic analysis methods for this type of data require cell segmentation and tracking which are challenging due to the high plasticity, lack of textures and frequent contacts between cells. To this end, we present a semi-supervised clustering algorithm for segmentation and tracking by grouping voxels according with a trainable grouping criterion. Moreover, we present novel analysis methods that do not require segmentation nor tracking. Speaker: Diego Ulisse Pizzagalli PhD Candidate and Teaching Assistant Institute for Research in Biomedicine - Bellinzona Institute of Computational Science, USI Host: Alessandro Giusti