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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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| Wydane w: | PeerJ Comput Sci |
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| Główni autorzy: | , , , , , , |
| Format: | Artigo |
| Język: | Inglês |
| Wydane: |
PeerJ Inc.
2021
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| Hasła przedmiotowe: | |
| Dostęp online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7924694/ https://ncbi.nlm.nih.gov/pubmed/33816999 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.7717/peerj-cs.349 |
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