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. 2021 Dec 21;11:24375. doi: 10.1038/s41598-021-03813-8

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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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(A) Single HFF-1 and HT-1080 cells are segmented based on defined localization classes. (B) Features were extracted from the entire data set of HFF-1 s and HT-1080 s images (whole cell, ~ 100 cells per line). Differences between these classes can be observed by eye and by statistically significant differences in features summarizing morphological and organizational properties. (C) Fisher discriminant analysis identified the most discriminatory features between these two data sets for all four localization classes.