COVLIAS 1.0 vs. MedSeg: Artificial Intelligence-Based Comparative Study for Automated COVID-19 Computed Tomography Lung Segmentation in Italian and Croatian Cohorts

(1) Background: COVID-19 computed tomography (CT) lung segmentation is critical for COVID lung severity diagnosis. Earlier proposed approaches during 2020–2021 were semiautomated or automated but not accurate, user-friendly, and industry-standard benchmarked. The proposed study compared the COVID Lu...

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Hauptverfasser:	Jasjit S. Suri, Sushant Agarwal, Alessandro Carriero, Alessio Paschè, Pietro S. C. Danna, Marta Columbu, Luca Saba, Klaudija Viskovic, Armin Mehmedović, Samriddhi Agarwal, Lakshya Gupta, Gavino Faa, Inder M. Singh, Monika Turk, Paramjit S. Chadha, Amer M. Johri, Narendra N. Khanna, Sophie Mavrogeni, John R. Laird, Gyan Pareek, Martin Miner, David W. Sobel, Antonella Balestrieri, Petros P. Sfikakis, George Tsoulfas, Athanasios Protogerou, Durga Prasanna Misra, Vikas Agarwal, George D. Kitas, Jagjit S. Teji, Mustafa Al-Maini, Surinder K. Dhanjil, Andrew Nicolaides, Aditya Sharma, Vijay Rathore, Mostafa Fatemi, Azra Alizad, Pudukode R. Krishnan, Ferenc Nagy, Zoltan Ruzsa, Archna Gupta, Subbaram Naidu, Kosmas I. Paraskevas, Mannudeep K. Kalra
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	MDPI AG 2021-12-01
Schriftenreihe:	Diagnostics
Schlagworte:	COVID-19 CT lung segmentation COVLIAS MedSeg AI
Online-Zugang:	https://www.mdpi.com/2075-4418/11/12/2367
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