Multicenter Study on COVID-19 Lung Computed Tomography Segmentation with varying Glass Ground Opacities using Unseen Deep Learning Artificial Intelligence Paradigms: COVLIAS 1.0 Validation

Variations in COVID-19 lesions such as glass ground opacities (GGO), consolidations, and crazy paving can compromise the ability of solo-deep learning (SDL) or hybrid-deep learning (HDL) artificial intelligence (AI) models in predicting automated COVID-19 lung segmentation in Computed Tomography (CT...

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Detalles Bibliográficos
Autores principales: Suri, Jasjit S., Agarwal, Sushant, Saba, Luca, Chabert, Gian Luca, Carriero, Alessandro, Paschè, Alessio, Danna, Pietro, Mehmedović, Armin, Faa, Gavino, Jujaray, Tanay, Singh, Inder M., Khanna, Narendra N., Laird, John R., Sfikakis, Petros P., Agarwal, Vikas, Teji, Jagjit S., R Yadav, Rajanikant, Nagy, Ferenc, Kincses, Zsigmond Tamás, Ruzsa, Zoltan, Viskovic, Klaudija, Kalra, Mannudeep K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Image & Signal Processing
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9392994/
https://www.ncbi.nlm.nih.gov/pubmed/35988110
http://dx.doi.org/10.1007/s10916-022-01850-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9392994/
https://www.ncbi.nlm.nih.gov/pubmed/35988110
http://dx.doi.org/10.1007/s10916-022-01850-y

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