Artificial Intelligence-based Fully Automated Per Lobe Segmentation and Emphysema-quantification Based on Chest Computed Tomography Compared With Global Initiative for Chronic Obstructive Lung Disease Severity of Smokers.
Journal:
Journal of thoracic imaging
Published Date:
May 1, 2020
Abstract
OBJECTIVES: The objective of this study was to evaluate an artificial intelligence (AI)-based prototype algorithm for the fully automated per lobe segmentation and emphysema quantification (EQ) on chest-computed tomography as it compares to the Global Initiative for Chronic Obstructive Lung Disease (GOLD) severity classification of chronic obstructive pulmonary disease (COPD) patients.
Authors
Keywords
Adult
Aged
Aged, 80 and over
Artificial Intelligence
Female
Humans
Lung
Male
Middle Aged
Pulmonary Disease, Chronic Obstructive
Pulmonary Emphysema
Radiographic Image Interpretation, Computer-Assisted
Radiography, Thoracic
Retrospective Studies
Severity of Illness Index
Smokers
Tomography, X-Ray Computed
Young Adult