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LTSP: long-term slice propagation for accurate airway segmentation
PURPOSE: Bronchoscopic intervention is a widely used clinical technique for pulmonary diseases, which requires an accurate and topological complete airway map for its localization and guidance. The airway map could be extracted from chest computed tomography (CT) scans automatically by airway segmen...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8924579/ https://www.ncbi.nlm.nih.gov/pubmed/35294715 http://dx.doi.org/10.1007/s11548-022-02582-7 |
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author | Wu, Yangqian Zhang, Minghui Yu, Weihao Zheng, Hao Xu, Jiasheng Gu, Yun |
author_facet | Wu, Yangqian Zhang, Minghui Yu, Weihao Zheng, Hao Xu, Jiasheng Gu, Yun |
author_sort | Wu, Yangqian |
collection | PubMed |
description | PURPOSE: Bronchoscopic intervention is a widely used clinical technique for pulmonary diseases, which requires an accurate and topological complete airway map for its localization and guidance. The airway map could be extracted from chest computed tomography (CT) scans automatically by airway segmentation methods. Due to the complex tree-like structure of the airway, preserving its topology completeness while maintaining the segmentation accuracy is a challenging task. METHODS: In this paper, a long-term slice propagation (LTSP) method is proposed for accurate airway segmentation from pathological CT scans. We also design a two-stage end-to-end segmentation framework utilizing the LTSP method in the decoding process. Stage 1 is used to generate a coarse feature map by an encoder–decoder architecture. Stage 2 is to adopt the proposed LTSP method for exploiting the continuity information and enhancing the weak airway features in the coarse feature map. The final segmentation result is predicted from the refined feature map. RESULTS: Extensive experiments were conducted to evaluate the performance of the proposed method on 70 clinical CT scans. The results demonstrate the considerable improvements of the proposed method compared to some state-of-the-art methods as most breakages are eliminated and more tiny bronchi are detected. The ablation studies further confirm the effectiveness of the constituents of the proposed method and the efficacy of the framework design. CONCLUSION: Slice continuity information is beneficial to accurate airway segmentation. Furthermore, by propagating the long-term slice feature, the airway topology connectivity is preserved with overall segmentation accuracy maintained. |
format | Online Article Text |
id | pubmed-8924579 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-89245792022-03-16 LTSP: long-term slice propagation for accurate airway segmentation Wu, Yangqian Zhang, Minghui Yu, Weihao Zheng, Hao Xu, Jiasheng Gu, Yun Int J Comput Assist Radiol Surg Original Article PURPOSE: Bronchoscopic intervention is a widely used clinical technique for pulmonary diseases, which requires an accurate and topological complete airway map for its localization and guidance. The airway map could be extracted from chest computed tomography (CT) scans automatically by airway segmentation methods. Due to the complex tree-like structure of the airway, preserving its topology completeness while maintaining the segmentation accuracy is a challenging task. METHODS: In this paper, a long-term slice propagation (LTSP) method is proposed for accurate airway segmentation from pathological CT scans. We also design a two-stage end-to-end segmentation framework utilizing the LTSP method in the decoding process. Stage 1 is used to generate a coarse feature map by an encoder–decoder architecture. Stage 2 is to adopt the proposed LTSP method for exploiting the continuity information and enhancing the weak airway features in the coarse feature map. The final segmentation result is predicted from the refined feature map. RESULTS: Extensive experiments were conducted to evaluate the performance of the proposed method on 70 clinical CT scans. The results demonstrate the considerable improvements of the proposed method compared to some state-of-the-art methods as most breakages are eliminated and more tiny bronchi are detected. The ablation studies further confirm the effectiveness of the constituents of the proposed method and the efficacy of the framework design. CONCLUSION: Slice continuity information is beneficial to accurate airway segmentation. Furthermore, by propagating the long-term slice feature, the airway topology connectivity is preserved with overall segmentation accuracy maintained. Springer International Publishing 2022-03-16 2022 /pmc/articles/PMC8924579/ /pubmed/35294715 http://dx.doi.org/10.1007/s11548-022-02582-7 Text en © CARS 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Original Article Wu, Yangqian Zhang, Minghui Yu, Weihao Zheng, Hao Xu, Jiasheng Gu, Yun LTSP: long-term slice propagation for accurate airway segmentation |
title | LTSP: long-term slice propagation for accurate airway segmentation |
title_full | LTSP: long-term slice propagation for accurate airway segmentation |
title_fullStr | LTSP: long-term slice propagation for accurate airway segmentation |
title_full_unstemmed | LTSP: long-term slice propagation for accurate airway segmentation |
title_short | LTSP: long-term slice propagation for accurate airway segmentation |
title_sort | ltsp: long-term slice propagation for accurate airway segmentation |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8924579/ https://www.ncbi.nlm.nih.gov/pubmed/35294715 http://dx.doi.org/10.1007/s11548-022-02582-7 |
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