ArticleRadiology. Cardiothoracic imaging2022
Airway Detection in COPD at Low-Dose CT Using Deep Learning and Multiparametric Freeze and Grow.
Article in Radiology. Cardiothoracic imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 8 citations in OpenAlex.
- Chest CT imaging toward personalized management of chronic obstructive pulmonary disease, asthma, and bronchiectasis: pulmonologist perspectives.Japanese journal of radiology · 2026Review
- Global trends and hotspots in AI applications for CT detection of chronic obstructive pulmonary disease: A bibliometric analysis from 2012 to 2024.Lasers in medical science · 2025Review
- Comorbidity of lung cancer and chronic obstructive pulmonary disease: correlation and optimization of treatment strategies.Translational lung cancer research · 2025Review
- Automated CT-based measurements of radial and longitudinal expansion of airways due to breathing-related lung volume change.Medical physics · 2025Article
- Automated CT-based decoupling of the effects of airway narrowing and wall thinning on airway counts in chronic obstructive pulmonary disease.The British journal of radiology · 2025Article
- Chest CT-based automated vertebral fracture assessment using artificial intelligence and morphologic features.Medical physics · 2024Article
- A Survey on Artificial Intelligence in Pulmonary Imaging.Wiley interdisciplinary reviews. Data mining and knowledge discoveryArticle
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Purpose: To present and validate a fully automated airway detection method at low-dose CT in patients with chronic obstructive pulmonary disease (COPD). Materials and Methods: In this retrospective study, deep learning (DL) and freeze-and-grow (FG) methods were optimized and applied to automatically detect airways at low-dose CT. Four data sets were used: two data sets consisting of matching standard- and low-dose CT scans from the Genetic Epidemiology of COPD (COPDGene) phase II (2014-2017) cohort ( Results: At low-dose CT, 56 294 of 62 480 (90.1%) airways of the reference total airway count (TAC) and 32 109 of 37 864 (84.8%) airways of the peripheral TAC (TAC Conclusion: A low-cost, automated CT-based airway detection method was suitable for investigation of airway phenotypes at low-dose CT.
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Registered trials
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