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Eight pruning deep learning models for low storage and high-speed COVID-19 computed tomography lung segmentation and heatmap-based lesion localization: A multicenter study using COVLIAS 2.0

BACKGROUND: COVLIAS 1.0: an automated lung segmentation was designed for COVID-19 diagnosis. It has issues related to storage space and speed. This study shows that COVLIAS 2.0 uses pruned AI (PAI) networks for improving both storage and speed, wiliest high performance on lung segmentation and lesio...

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Detalles Bibliográficos
Autores principales: Agarwal, Mohit, Agarwal, Sushant, Saba, Luca, Chabert, Gian Luca, Gupta, Suneet, Carriero, Alessandro, Pasche, Alessio, Danna, Pietro, Mehmedovic, Armin, Faa, Gavino, Shrivastava, Saurabh, Jain, Kanishka, Jain, Harsh, Jujaray, Tanay, Singh, Inder M., Turk, Monika, Chadha, Paramjit S., Johri, Amer M., Khanna, Narendra N., Mavrogeni, Sophie, Laird, John R., Sobel, David W., Miner, Martin, Balestrieri, Antonella, Sfikakis, Petros P., Tsoulfas, George, Misra, Durga Prasanna, Agarwal, Vikas, Kitas, George D., Teji, Jagjit S., Al-Maini, Mustafa, Dhanjil, Surinder K., Nicolaides, Andrew, Sharma, Aditya, Rathore, Vijay, Fatemi, Mostafa, Alizad, Azra, Krishnan, Pudukode R., Yadav, Rajanikant R., Nagy, Frence, Kincses, Zsigmond Tamás, Ruzsa, Zoltan, Naidu, Subbaram, Viskovic, Klaudija, Kalra, Manudeep K., Suri, Jasjit S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9123805/
https://www.ncbi.nlm.nih.gov/pubmed/35751196
http://dx.doi.org/10.1016/j.compbiomed.2022.105571