Latent traits of lung tissue patterns in former smokers derived by dual channel deep learning in computed tomography images

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease and the traditional variables extracted from computed tomography (CT) images may not be sufficient to describe all the topological features of lung tissues in COPD patients. We employed an unsupervised three-dimensional (3D) con...

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Vydané v:	Scientific reports Ročník 11; číslo 1; s. 4916 - 15
Hlavní autori:	Li, Frank, Choi, Jiwoong, Zou, Chunrui, Newell, John D., Comellas, Alejandro P., Lee, Chang Hyun, Ko, Hongseok, Barr, R. Graham, Bleecker, Eugene R., Cooper, Christopher B., Abtin, Fereidoun, Barjaktarevic, Igor, Couper, David, Han, MeiLan, Hansel, Nadia N., Kanner, Richard E., Paine, Robert, Kazerooni, Ella A., Martinez, Fernando J., O’Neal, Wanda, Rennard, Stephen I., Smith, Benjamin M., Woodruff, Prescott G., Hoffman, Eric A., Lin, Ching-Long
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	London Nature Publishing Group UK 01.03.2021 Nature Publishing Group Nature Portfolio
Predmet:	639/166/985 692/699/1785/4037 Adult Aged Case-Control Studies Chronic obstructive pulmonary disease Cohort Studies Computed tomography Deep learning Emphysema Factor analysis Female Humanities and Social Sciences Humans Lung - diagnostic imaging Lung - pathology Lung diseases Male Middle Aged multidisciplinary Obstructive lung disease Phenotypes Pulmonary Disease, Chronic Obstructive - diagnostic imaging Respiratory tract Science Science (multidisciplinary) Smokers Subpopulations Tomography Tomography, X-Ray Computed - methods
ISSN:	2045-2322, 2045-2322
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