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. 2022 Jun 18;12:10296. doi: 10.1038/s41598-022-14042-y

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© The Author(s) 2022

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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Virtual Staining framework. Pairs of TA-PARS and H&E images are co-registered to create the training dataset, which is then used to train the Pix2Pix³⁹ model. Unseen TA-PARS images are then fed into the trained model for virtual staining, producing H&E-like visualizations. Scale bar: 50 µm.