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. 2018 Jun 28;8:9802. doi: 10.1038/s41598-018-28100-x

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© The Author(s) 2018

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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Automatic lung segmentation pipeline: (a) Source chest CT volume; (b) 3D rendering of the air-like structures detected in the image using automatic adaptive thresholding; (c) 3D rendering of the preliminary lung and connected airways segmentation obtained using a set of topological operations based on the position of all pre-segmented structures; (d) Isolated airways tree extracted with a propagating wavefront approach; (e) axial slice of the final lung segmentation in which the lesions caused by Mtb and attached to the pleura have been included and the motion artifacts discarded; (f) 3D rendering of the final lung segmentation including healthy parenchyma, the damaged parenchyma and the blood vessels.