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Topological Data Analysis (TDA) extracts and analyzes the underlying topological structures of data. Recent years has witnessed much progress, including efficient algorithms for persistence diagrams and effective kernel methods. Applying such tools in practice is exciting yet still nontrivial. In this presentation, we will describe our use of topological features for the analysis of various biomedical images, highlighting promises and limitations of the currently available methods.
This presentation is part of Minisymposium “MS16 - Topological Image Analysis: Methods, Algorithms, Applications (3 parts)”
organized by: Patrizio Frosini (University of Bologna) , Massimo Ferri (University of Bologna) , Claudia Landi (University of Modena and Reggio Emilia) .