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Extraction of pulmonary Trachea by dynamic tubular edge contour algorithm

BACKGROUND: One of the difficulties and hot topics in the field of computer vision and image processing is extraction of the high-level pulmonary trachea from patients’ lung CT images. Current, common bronchial extraction methods are limited by the phenomenon of bronchial loss and leakage, and canno...

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Autores principales: Fan, Qing-Wen, Pei, Hong-Liang, Luo, Feng-Ming, Li, Xiao-Ou, Wang, Ke, Jiang, Wen-Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7812215/
https://www.ncbi.nlm.nih.gov/pubmed/33490148
http://dx.doi.org/10.21037/atm-20-7300
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author Fan, Qing-Wen
Pei, Hong-Liang
Luo, Feng-Ming
Li, Xiao-Ou
Wang, Ke
Jiang, Wen-Jun
author_facet Fan, Qing-Wen
Pei, Hong-Liang
Luo, Feng-Ming
Li, Xiao-Ou
Wang, Ke
Jiang, Wen-Jun
author_sort Fan, Qing-Wen
collection PubMed
description BACKGROUND: One of the difficulties and hot topics in the field of computer vision and image processing is extraction of the high-level pulmonary trachea from patients’ lung CT images. Current, common bronchial extraction methods are limited by the phenomenon of bronchial loss and leakage, and cannot extract the higher-level pulmonary trachea, which does not meet the requirements of guiding lung puncture procedures. METHODS: Based on the characteristic “tubular structure” (ring or semi-closed ring) of the pulmonary trachea in CT images, an algorithm based on dynamic tubular edge contour is proposed. In axial, coronal and sagittal CT images, the algorithm could extract the skeletal line of the pulmonary trachea and vessel-connecting region, perform elliptical fitting, extract the pulmonary trachea by the ratio of the ellipse’s long and short axes, and obtain point cloud data of the pulmonary trachea in three directions. The point cloud data was fused to obtain a complete three-dimensional model of the pulmonary trachea. RESULTS: The algorithm was verified using CT data from “EXACT09”, and could extract the pulmonary trachea to the 10–11 level, which effectively solves the problems of leakage and loss of the trachea. CONCLUSIONS: We have constructed a novel extraction algorithm of pulmonary trachea that can guide the doctors to decide the puncture path and avoid the large trachea, which has important theoretical and practical significance for reducing puncture complications and the mortality rate.
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spelling pubmed-78122152021-01-22 Extraction of pulmonary Trachea by dynamic tubular edge contour algorithm Fan, Qing-Wen Pei, Hong-Liang Luo, Feng-Ming Li, Xiao-Ou Wang, Ke Jiang, Wen-Jun Ann Transl Med Original Article BACKGROUND: One of the difficulties and hot topics in the field of computer vision and image processing is extraction of the high-level pulmonary trachea from patients’ lung CT images. Current, common bronchial extraction methods are limited by the phenomenon of bronchial loss and leakage, and cannot extract the higher-level pulmonary trachea, which does not meet the requirements of guiding lung puncture procedures. METHODS: Based on the characteristic “tubular structure” (ring or semi-closed ring) of the pulmonary trachea in CT images, an algorithm based on dynamic tubular edge contour is proposed. In axial, coronal and sagittal CT images, the algorithm could extract the skeletal line of the pulmonary trachea and vessel-connecting region, perform elliptical fitting, extract the pulmonary trachea by the ratio of the ellipse’s long and short axes, and obtain point cloud data of the pulmonary trachea in three directions. The point cloud data was fused to obtain a complete three-dimensional model of the pulmonary trachea. RESULTS: The algorithm was verified using CT data from “EXACT09”, and could extract the pulmonary trachea to the 10–11 level, which effectively solves the problems of leakage and loss of the trachea. CONCLUSIONS: We have constructed a novel extraction algorithm of pulmonary trachea that can guide the doctors to decide the puncture path and avoid the large trachea, which has important theoretical and practical significance for reducing puncture complications and the mortality rate. AME Publishing Company 2020-12 /pmc/articles/PMC7812215/ /pubmed/33490148 http://dx.doi.org/10.21037/atm-20-7300 Text en 2020 Annals of Translational Medicine. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Original Article
Fan, Qing-Wen
Pei, Hong-Liang
Luo, Feng-Ming
Li, Xiao-Ou
Wang, Ke
Jiang, Wen-Jun
Extraction of pulmonary Trachea by dynamic tubular edge contour algorithm
title Extraction of pulmonary Trachea by dynamic tubular edge contour algorithm
title_full Extraction of pulmonary Trachea by dynamic tubular edge contour algorithm
title_fullStr Extraction of pulmonary Trachea by dynamic tubular edge contour algorithm
title_full_unstemmed Extraction of pulmonary Trachea by dynamic tubular edge contour algorithm
title_short Extraction of pulmonary Trachea by dynamic tubular edge contour algorithm
title_sort extraction of pulmonary trachea by dynamic tubular edge contour algorithm
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7812215/
https://www.ncbi.nlm.nih.gov/pubmed/33490148
http://dx.doi.org/10.21037/atm-20-7300
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