The Spatial Analysis for Biological Imaging workshop will be held at the Department of Mathematics, Imperial College London, South Kensington Campus, London, UK between March 29-30, 2023.
Workshop Aim: Imaging technologies play an ever increasing role in biomedical and clinical investigations as they allow the observation of important spatial processes. While such imaging approaches have undergone major technological developments through, for example, the development of novel detectors and sample preparation approaches, the analysis of the resulting data has often lagged behind. This is even more problematic as the amount of data that can and is being generated is very large.
Methods for spatial analysis, including spatial statistics, machine learning, and topological data analysis, hold significant promise to be able to resolve many outstanding analytical problems. The purpose of this workshop is to provide a means for leading researchers in bioimaging, digital pathology and histology to present their latest findings and also to, for the first time, bring these communities together as it is expected that exchange of ideas could be of major benefit to all sides.
Confirmed invited speakers:
Carolina Wählby, Uppsala University (Visualization, interaction, and unsupervised quantification – key components in large-scale spatial omics)
Dylan Owen, University of Birmingham (Community-based, nanoscale mapping of biomolecules in cells)
Thibault Lagache, Institut Pasteur (Interrogating the organization of biological processes at different scales with spatial statistics)
Anthea Monod, Imperial College London (Topological imaging summary statistics for GBM)
Anca Grapa, Institute of Cancer Research, London (Characterization of growth pattern landscape in lung adenocarcinoma using artificial intelligence and spatial intermixing networks)
Daniel Davis, Imperial College London (Watching immune cells kill)
Sripad Ram, Pfizer, San Diego (From macro to micro: 3D spatiotemporal analysis of nanoparticles in tumour tissue using VIOLA technology)
Susan Cox, King’s College London (From images to information: enhancing resolution and improving accuracy in SMLM)
Ed Cohen, Imperial College London (Spatial point patterns: 101 to manifolds)
Lekha Patel, Sandia National Laboratories, New Mexico (Spatial-temporal modeling for nanoscale resolvement of photo-switching fluorophores)
Christian Schürch, Institute of Pathology, University Hospital Tübingen, Germany (Deconstructing disease mechanisms, therapy responses and patient outcomes by highly multiplexed tissue imaging)
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