Persistent entropy: a scale-invariant topological statistic for analyzing cell arrangements
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In this work, we explain how to use computational topology for detecting differences in the geometrical distribution of cells forming epithelial tissues. In particular, we extract topological information from images using persistent homology and summarize it with a number called persistent entropy. This method is scale invariant, robust to noise and sensitive to global topological features of the tissue. We have found significant differences between chick neuroepithelium and epithelium of Drosophila wing discs in both, larva and prepupal stages.
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