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. 2022 Mar 23;12:5002. doi: 10.1038/s41598-022-08351-5

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© The Author(s) 2022

Open AccessThis 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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(A) Left: Kernel Density Estimation (KDE) plot of 2D PCA feature space for 16000 random patches extracted from ProMPT, TCGA and FOCUS cohorts. Whilst there is still room for improvement, the overlap between feature spaces of different cohorts suggests that we have a reasonable domain-invariant set of features. Right: Feature space of annotated patches in our patch test set from ProMPT cohort vs a set of annotated patches from TCGA and FOCUS cohorts. (B) Sample image patches predicted by PathProfiler as unusable from non-prostate tissue (FOCUS colorectal tissue) and TCGA (prostate tissue) cohorts.