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COVLIAS 3.0: cloud-based quantized hybrid UNet3+ deep learning for COVID-19 lesion detection in lung computed tomography

Background and noveltyWhen RT-PCR is ineffective in early diagnosis and understanding of COVID-19 severity, Computed Tomography (CT) scans are needed for COVID diagnosis, especially in patients having high ground-glass opacities, consolidations, and crazy paving. Radiologists find the manual method...

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Principais autores: Sushant Agarwal, Sanjay Saxena, Alessandro Carriero, Gian Luca Chabert, Gobinath Ravindran, Sudip Paul, John R. Laird, Deepak Garg, Mostafa Fatemi, Lopamudra Mohanty, Arun K. Dubey, Rajesh Singh, Mostafa M. Fouda, Narpinder Singh, Subbaram Naidu, Klaudija Viskovic, Melita Kukuljan, Manudeep K. Kalra, Luca Saba, Jasjit S. Suri
Format: Artigo
Sprog:Inglês
Udgivet: Frontiers Media S.A. 2024-06-01
Serier:Frontiers in Artificial Intelligence
Fag:
COVID-19
computed tomography
COVID lesions
glass ground opacities
segmentation
hybrid deep learning
Online adgang:https://www.frontiersin.org/articles/10.3389/frai.2024.1304483/full
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