A radiographic, deep transfer learning framework, adapted to estimate lung opacities from chest x-rays

A radiographic, deep transfer learning framework, adapted to estimate lung opacities from chest x-rays

Abstract Chest radiographs (CXRs) are the most widely available radiographic imaging modality used to detect respiratory diseases that result in lung opacities. CXR reports often use non-standardized language that result in subjective, qualitative, and non-reproducible opacity estimates. Our goal wa...

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Bibliographic Details
Main Authors: Avantika Vardhan, Alex Makhnevich, Pravan Omprakash, David Hirschorn, Matthew Barish, Stuart L. Cohen, Theodoros P. Zanos
Format: Article
Language:English
Published: BMC 2023-01-01
Series:Bioelectronic Medicine
Subjects:
Chest X-ray (CXR)
Deep transfer learning
Heatmap concordance
Lung opacity
Ordinal classification
Pretrained model
Online Access:https://doi.org/10.1186/s42234-022-00103-0

Internet

https://doi.org/10.1186/s42234-022-00103-0

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