Quantitative Evaluation of Airway Lesions in Chronic Obstructive Pulmonary Disease by Applying Deep Learning Reconstruction to Ultra-high-resolution CT Images: Correlation between Wall Area Percentage and Forced Expiratory Volume in One Second Percentage-Reference-Cited by-同舟云学术

Quantitative Evaluation of Airway Lesions in Chronic Obstructive Pulmonary Disease by Applying Deep Learning Reconstruction to Ultra-high-resolution CT Images: Correlation between Wall Area Percentage and Forced Expiratory Volume in One Second Percentage

Published:2022 Issue:10 Volume:78 Page:1167-1175
ISSN:0369-4305
Container-title:Japanese Journal of Radiological Technology
language:en
Short-container-title:Nippon Hoshasen Gijutsu Gakkai Zasshi

Author:

Muramatsu Shun¹,Sato Kazuhiro²

Affiliation:

1. Department of Radiology, Ohara General Hospital

2. Faculty of Health Sciences, Hokkaido University of Science

Publisher

Japanese Society of Radiological Technology

Subject

General Medicine

Link

https://www.jstage.jst.go.jp/article/jjrt/78/10/78_2022-1271/_pdf

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4. 4） Hogg JC, Macklem PT, Thurlbeck WM. Site and nature of airway obstruction in chronic obstructive lung disease. N Engl J Med 1968; 278(25): 1355–1360.

5. 5） de Jong PA, Muller NL, Pare PD, et al. Computed tomographic imaging of the airways: relationship to structure and function. Eur Respir J 2005; 26(1): 140–152.