Longitudinal assessment of interstitial lung abnormalities on CT in patients with COPD using artificial intelligence-based segmentation: a prospective observational study
Yusuke Shiraishi,
Naoya Tanabe,
Ryo Sakamoto
et al.
Abstract:Background
Interstitial lung abnormalities (ILAs) on CT may affect the clinical outcomes in patients with chronic obstructive pulmonary disease (COPD), but their quantification remains unestablished. This study examined whether artificial intelligence (AI)-based segmentation could be applied to identify ILAs using two COPD cohorts.
Methods
ILAs were diagnosed visually based on the Fleischner Society definition. Using an AI-based method, ground-glas… Show more
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