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. 2021 Aug 6;11:16001. doi: 10.1038/s41598-021-95364-1

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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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Schematics of the proposed airway segmentation method. (a) Overview at training time, showing the extraction of 3D random patches from the CT scan, to feed as input to the U-Net. (b) Overview at testing time, showing the extraction of 3D patches through sliding-window, and the generation of the airway tree segmentation from the patch-wise output of the U-Net.