ADID-UNET—a segmentation model for COVID-19 infection from lung CT scans

Currently, the new coronavirus disease (COVID-19) is one of the biggest health crises threatening the world. Automatic detection from computed tomography (CT) scans is a classic method to detect lung infection, but it faces problems such as high variations in intensity, indistinct edges near lung in...

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Detalles Bibliográficos
Autores principales: Joseph Raj, Alex Noel, Zhu, Haipeng, Khan, Asiya, Zhuang, Zhemin, Yang, Zengbiao, Mahesh, Vijayalakshmi G. V., Karthik, Ganesan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2021
Materias:
Human-Computer Interaction
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7924694/
https://www.ncbi.nlm.nih.gov/pubmed/33816999
http://dx.doi.org/10.7717/peerj-cs.349

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7924694/
https://www.ncbi.nlm.nih.gov/pubmed/33816999
http://dx.doi.org/10.7717/peerj-cs.349

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