Lung Segmentation and Characterization in COVID-19 Patients for Assessing Pulmonary Thromboembolism: An Approach Based on Deep Learning and Radiomics

Lung Segmentation and Characterization in COVID-19 Patients for Assessing Pulmonary Thromboembolism: An Approach Based on Deep Learning and Radiomics

The COVID-19 pandemic is inevitably changing the world in a dramatic way, and the role of computed tomography (CT) scans can be pivotal for the prognosis of COVID-19 patients. Since the start of the pandemic, great care has been given to the relationship between interstitial pneumonia caused by the...

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Bibliographic Details
Main Authors: Vitoantonio Bevilacqua, Nicola Altini, Berardino Prencipe, Antonio Brunetti, Laura Villani, Antonello Sacco, Chiara Morelli, Michele Ciaccia, Arnaldo Scardapane
Format: Article
Language:English
Published: MDPI AG 2021-10-01
Series:Electronics
Subjects:
COVID-19
lung segmentation
lesion segmentation
deep learning
radiomics
pulmonary thromboembolism
Online Access:https://www.mdpi.com/2079-9292/10/20/2475

Internet

https://www.mdpi.com/2079-9292/10/20/2475

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