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

Suri Jasjit S. and Agarwal Sushant and Saba Luca and Chabert Gian Luca and Carriero Alessandro and Paschè Alessio and Danna Pietro and Mehmedović Armin and Faa Gavino and Jujaray Tanay and Singh Inder M. and Khanna Narendra N. and Laird John R. and Nagy Ferenc Tamás and Kincses Zsigmond Tamás and Ruzsa Zoltán: 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.
JOURNAL OF MEDICAL SYSTEMS, 46 (10). Terjedelem: 29 p.-Azonosító: 62. ISSN 0148-5598 (2022)

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Item Type: Journal Article
Szerzők száma: 22
Journal or Publication Title: JOURNAL OF MEDICAL SYSTEMS
Date: 2022
Volume: 46
Number: 10
Page Range: Terjedelem: 29 p.-Azonosító: 62
ISSN: 0148-5598
Faculty/Unit: Albert Szent-Györgyi Medical School
Institution: Szegedi Tudományegyetem
Language: English
MTMT rekordazonosító: 33073852
DOI azonosító: https://doi.org/10.1007/s10916-022-01850-y
Date Deposited: 2022. Sep. 01. 09:04
Last Modified: 2022. Sep. 01. 09:04
URI: http://publicatio.bibl.u-szeged.hu/id/eprint/24985
Web of Science® Times Cited: 8 View citing articles in Web of Science®

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