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. 2021 Apr 9;51:4. doi: 10.1186/s42649-021-00053-y

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© The Author(s) 2021

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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Fig. 1 — Workflow of tissue sectioning, staining and scanning. Serial sectioning of FFPE tissue blocks was used for H&E or IHC staining in order to characterize the region of interest. H&E and IHC slides were scanned at wide-field mode with 20× water immersion objective at a single layer. ROIs on FISH slides were scanned at confocal mode with multiple layers (N = 7 layers at 0.6 μm interval) with 40× water immersion objective and a final image resolution of 0.16 μm/pixel. Three filters were chosen: DAPI (blue), FITC (green) and TRITC (red). Showing in a dashed line frame: we are currently developing a deep learning algorithm for an automated tumor area detection