Dealing with Topological Information within a Fully Convolutional Neural Network

Etienne Decencière; Santiago Velasco-Forero; Fu Min; Juanjuan Chen; Hélène Burdin; Gervais Gauthier; Bruno Laÿ; Thomas Bornschloegl; Thérèse Baldeweck

doi:10.1007/978-3-030-01449-0_39

arXiv · 1906.11600

Dealing with Topological Information within a Fully Convolutional Neural Network

Etienne Decencière·Santiago Velasco-Forero·Fu Min·Juanjuan Chen·Hélène Burdin·Gervais Gauthier·Bruno Laÿ·Thomas Bornschloegl·Thérèse Baldeweck

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Abstract

A fully convolutional neural network has a receptive field of limited size and therefore cannot exploit global information, such as topological information. A solution is proposed in this paper to solve this problem, based on pre-processing with a geodesic operator. It is applied to the segmentation of histological images of pigmented reconstructed epidermis acquired via Whole Slide Imaging.

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Etienne Decencière, Santiago Velasco-Forero, Fu Min, Juanjuan Chen, Hélène Burdin, Gervais Gauthier, Bruno Laÿ, Thomas Bornschloegl, Thérèse Baldeweck. 2019-06-27. Dealing with Topological Information within a Fully Convolutional Neural Network. https://doi.org/10.1007/978-3-030-01449-0_39

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