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. 2019 Feb 6;9:1483. doi: 10.1038/s41598-018-37638-9

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© The Author(s) 2019

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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

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Classification of LAC tumor growth patterns in digital slides. Slides classified by CNNs are outputted as colored maps showing the growth pattern and location of solid, micropapillary, acinar, and cribriform tumor growth patterns. Middle column: maps outputted by FT-AlexNet, right column: maps outputted by DN-AlexNet. Reference annotations by pathologists are shown in the leftmost column. Example slides are from (A) CSMC, (B) MIMW and (C) TCGA cohorts. Pathologist’s annotations and computer-generated maps were overlaid to calculate measures of CNN performance.