Artificial intelligence for differentiating COVID-19 from other viral pneumonias on CT: comparative analysis of different models based on quantitative and radiomic approaches

Artificial intelligence for differentiating COVID-19 from other viral pneumonias on CT: comparative analysis of different models based on quantitative and radiomic approaches

Abstract Background To develop a pipeline for automatic extraction of quantitative metrics and radiomic features from lung computed tomography (CT) and develop artificial intelligence (AI) models supporting differential diagnosis between coronavirus disease 2019 (COVID-19) and other viral pneumonia...

Full description

Bibliographic Details
Main Authors: Giulia Zorzi, Luca Berta, Francesco Rizzetto, Cristina De Mattia, Marco Maria Jacopo Felisi, Stefano Carrazza, Silvia Nerini Molteni, Chiara Vismara, Francesco Scaglione, Angelo Vanzulli, Alberto Torresin, Paola Enrica Colombo
Format: Article
Language:English
Published: SpringerOpen 2023-01-01
Series:European Radiology Experimental
Subjects:
Artificial intelligence
COVID-19
Lung
Radiomics
Tomography (x-ray
computed)
Online Access:https://doi.org/10.1186/s41747-022-00317-6

Similar Items

Similar Items