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D2A U-Net: Automatic segmentation of COVID-19 CT slices based on dual attention and hybrid dilated convolution
Coronavirus Disease 2019 (COVID-19) has become one of the most urgent public health events worldwide due to its high infectivity and mortality. Computed tomography (CT) is a significant screening tool for COVID-19 infection, and automatic segmentation of lung infection in COVID-19 CT images can assi...
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| Pubblicato in: | Comput Biol Med |
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| Autori principali: | , , , , , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Elsevier Ltd.
2021
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8169238/ https://ncbi.nlm.nih.gov/pubmed/34146799 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.compbiomed.2021.104526 |
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