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. 2021 Nov 29;11:23041. doi: 10.1038/s41598-021-02441-6

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© The Author(s) 2021

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Hoescht staining improves the sensitivity to discriminate tumor progression. Representative crop of an H&E-stained (a) and Hoescht stained (b) tissue biopsy image (left). Marked in blue are the regions detected as nuclei for downstream segmentation and analysis. Representative crops of individual nuclei segmented are shown on the right side. Confusion matrices depicting the performances of the linear discriminant classifier in classifying nuclei from normal and metastatic tissues according to their nuclear features in H&E-stained tissues (c) and Hoescht stained tissues (d). (e) Correlation between nuclear features and the linear discriminant axis for the Hoescht-stained nuclei. The features have been colour-coded and grouped into morphological features, mixed features and intensity features.