PyHIST: A Histological Image Segmentation Tool

Muñoz-Aguirre, Manuel; Ntasis, Vasilis F.; Rojas, Santiago; Guigó Serra, Roderic

doi:http://dx.doi.org/10.1371/journal.pcbi.1008349

PyHIST: A Histological Image Segmentation Tool

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Muñoz-Aguirre M, Ntasis VF, Rojas S, Guigó R. PyHIST: A Histological Image Segmentation Tool. PLoS Comput Biol. 2020; 16(10):e1008349. DOI: 10.1371/journal.pcbi.1008349

Abstract

The development of increasingly sophisticated methods to acquire high-resolution images has led to the generation of large collections of biomedical imaging data, including images of tissues and organs. Many of the current machine learning methods that aim to extract biological knowledge from histopathological images require several data preprocessing stages, creating an overhead before the proper analysis. Here we present PyHIST (https://github.com/manuel-munoz-aguirre/PyHIST), an easy-to-use, open source whole slide histological image tissue segmentation and preprocessing command-line tool aimed at tile generation for machine learning applications. From a given input image, the PyHIST pipeline i) optionally rescales the image to a different resolution, ii) produces a mask for the input image which separates the background from the tissue, and iii) generates individual image tiles with tissue content.