AI Lung Segmentation and Perfusion Analysis of Dual-Energy CT Can Help to Distinguish COVID-19 Infiltrates from Visually Similar Immunotherapy-Related Pneumonitis Findings and Can Optimize Radiological Workflows

AI Lung Segmentation and Perfusion Analysis of Dual-Energy CT Can Help to Distinguish COVID-19 Infiltrates from Visually Similar Immunotherapy-Related Pneumonitis Findings and Can Optimize Radiological Workflows

(1) To explore the potential impact of an AI dual-energy CT (DECT) prototype on decision making and workflows by investigating its capabilities to differentiate COVID-19 from immunotherapy-related pneumonitis. (2) Methods: From 3 April 2020 to 12 February 2021, DECT from biometrically matching patie...

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Bibliographic Details
Main Authors: Andreas S. Brendlin, Markus Mader, Sebastian Faby, Bernhard Schmidt, Ahmed E. Othman, Sebastian Gassenmaier, Konstantin Nikolaou, Saif Afat
Format: Article
Language:English
Published: MDPI AG 2021-12-01
Series:Tomography
Subjects:
COVID-19
dual energy
tomography
X-ray computed
artificial intelligence
Online Access:https://www.mdpi.com/2379-139X/8/1/3

Internet

https://www.mdpi.com/2379-139X/8/1/3

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