Emphysema Progression at CT by Deep Learning Predicts Functional Impairment and Mortality: Results from the COPDGene Study-Reference-Cited by-同舟云学术

Emphysema Progression at CT by Deep Learning Predicts Functional Impairment and Mortality: Results from the COPDGene Study

Published:2022-09 Issue:3 Volume:304 Page:672-679
ISSN:0033-8419
Container-title:Radiology
language:en
Short-container-title:Radiology

Author:

Oh Andrea S.¹^ORCID,Baraghoshi David¹^ORCID,Lynch David A.¹^ORCID,Ash Samuel Y.¹^ORCID,Crapo James D.¹^ORCID,Humphries Stephen M.¹^ORCID,

Affiliation:

1. From the Departments of Radiology (A.S.O., D.A.L., S.M.H.) and Biostatistics (D.B.) and Division of Pulmonary and Critical Care Medicine, Department of Medicine (J.D.C.), National Jewish Health, 1400 Jackson St, Denver, CO 80206; and Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, Mass (S.Y.A.).

Funder

National Heart, Lung, and Blood Institute

Publisher

Radiological Society of North America (RSNA)

Subject

Radiology, Nuclear Medicine and imaging

Link

http://pubs.rsna.org/doi/pdf/10.1148/radiol.213054

Reference34 articles.

1. Diagnosis and Management of Stable Chronic Obstructive Pulmonary Disease: A Clinical Practice Guideline Update from the American College of Physicians, American College of Chest Physicians, American Thoracic Society, and European Respiratory Society

2. “Density Mask”

3. Pulmonary Emphysema: Objective Quantification at Multi–Detector Row CT—Comparison with Macroscopic and Microscopic Morphometry