Automated CT Staging of Chronic Obstructive Pulmonary Disease Severity for Predicting Disease Progression and Mortality with a Deep Learning Convolutional Neural Network

PURPOSE: To develop a deep learning–based algorithm to stage the severity of chronic obstructive pulmonary disease (COPD) through quantification of emphysema and air trapping on CT images and to assess the ability of the proposed stages to prognosticate 5-year progression and mortality. MATERIALS AN...

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Bibliographic Details
Published in:Radiol Cardiothorac Imaging
Main Authors: Hasenstab, Kyle A., Yuan, Nancy, Retson, Tara, Conrad, Douglas J., Kligerman, Seth, Lynch, David A., Hsiao, Albert
Format: Artigo
Language:Inglês
Published: Radiological Society of North America 2021
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Original Research
Online Access:https://ncbi.nlm.nih.gov/pmc/articles/PMC8098086/
https://ncbi.nlm.nih.gov/pubmed/33969307
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1148/ryct.2021200477
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