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

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

Abstract 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...

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Autores principales: Frank Li, Jiwoong Choi, Chunrui Zou, John D. Newell, Alejandro P. Comellas, Chang Hyun Lee, Hongseok Ko, R. Graham Barr, Eugene R. Bleecker, Christopher B. Cooper, Fereidoun Abtin, Igor Barjaktarevic, David Couper, MeiLan Han, Nadia N. Hansel, Richard E. Kanner, Robert Paine, Ella A. Kazerooni, Fernando J. Martinez, Wanda O’Neal, Stephen I. Rennard, Benjamin M. Smith, Prescott G. Woodruff, Eric A. Hoffman, Ching-Long Lin
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
Materias:
Medicine
R
Science
Q
Acceso en línea:https://doaj.org/article/c5e067c40faa40fa966e6aa8bc55c3f2
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