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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Bibliografiska uppgifter

Huvudupphov:	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
Materialtyp:	Artigo
Språk:	Inglês
Utgiven:	Frontiers Media S.A. 2024-06-01
Serie:	Frontiers in Artificial Intelligence
Ämnen:	COVID-19 computed tomography COVID lesions glass ground opacities segmentation hybrid deep learning
Länkar:	https://www.frontiersin.org/articles/10.3389/frai.2024.1304483/full
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