Characterising epithelial tissues using persistent entropy

10/13/2018
by   N. Atienza, et al.
0

In this paper, we apply persistent entropy, a novel topological statistic, for characterization of images of epithelial tissues. We have found out that persistent entropy is able to summarize topological and geometric information encoded by α-complexes and persistent homology. After using some statistical tests, we can guarantee the existence of significant differences in the studied tissues.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
02/18/2019

Persistent entropy: a scale-invariant topological statistic for analyzing cell arrangements

In this work, we explain how to use computational topology for detecting...
research
12/06/2022

Persistent Homology of Chromatic Alpha Complexes

Motivated by applications in medical sciences, we study finite chromatic...
research
05/01/2021

Topological Data Analysis of COVID-19 Virus Spike Proteins

Topological data analysis, including persistent homology, has undergone ...
research
08/14/2018

Complexity of Shift Spaces on Semigroups

Let G=〈 S|R_A〉 be a semigroup with generating set S and equivalences R...
research
02/18/2018

Algorithmic Information Dynamics of Persistent Patterns and Colliding Particles in the Game of Life

We demonstrate the way to apply and exploit the concept of algorithmic i...
research
11/28/2017

Adversary Detection in Neural Networks via Persistent Homology

We outline a detection method for adversarial inputs to deep neural netw...

Please sign up or login with your details

Forgot password? Click here to reset