Improved detection of air trapping on expiratory computed tomography using deep learning

BACKGROUND: Radiologic evidence of air trapping (AT) on expiratory computed tomography (CT) scans is associated with early pulmonary dysfunction in patients with cystic fibrosis (CF). However, standard techniques for quantitative assessment of AT are highly variable, resulting in limited efficacy fo...

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Detalhes bibliográficos
Publicado no:PLoS One
Main Authors: Ram, Sundaresh, Hoff, Benjamin A., Bell, Alexander J., Galban, Stefanie, Fortuna, Aleksa B., Weinheimer, Oliver, Wielpütz, Mark O., Robinson, Terry E., Newman, Beverley, Vummidi, Dharshan, Chughtai, Aamer, Kazerooni, Ella A., Johnson, Timothy D., Han, MeiLan K., Hatt, Charles R., Galban, Craig J.
Formato: Artigo
Idioma:Inglês
Publicado em: Public Library of Science 2021
Assuntos:
Research Article
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC7990199/
https://ncbi.nlm.nih.gov/pubmed/33760861
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0248902
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