| Knowledge4COVID-19

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?:authorAffiliation	[\'Scuola Normale Superiore, Pisa, Italy. francesca.lizzi@sns.it.\', \'National Institute of Nuclear Physics (INFN), Pisa division, Pisa, Italy. francesca.lizzi@sns.it.\', \'Department of Mathematics, University of Pavia, Pavia, Italy.\', \'INFN, Pavia division, Pavia, Italy.\', \'Department of Physics, University of Pavia, Pavia, Italy.\', \'National Institute of Nuclear Physics (INFN), Pisa division, Pisa, Italy.\', \'Department of Physics, University of Pisa, Pisa, Italy.\', \'Department of Social and Political Science, University of Pavia, Pavia, Italy.\', \'Scuola Normale Superiore, Pisa, Italy.\', \'Department of Chemistry and Pharmacy, University of Sassari, Sassari, Italy.\', \'INFN, Cagliari division, Cagliari, Italy.\', \'Department of Biomedical Experimental Clinical Science \'M. Serio\', University of Florence, Florence, Italy.\', \'INFN, Florence division, Florence, Italy.\']
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?:doi	10.1007/s11548-021-02501-2
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?:title	Quantification of pulmonary involvement in COVID-19 pneumonia by means of a cascade of two U-nets: training and assessment on multiple datasets using different annotation criteria.
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?:year	2022

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Quantification of pulmonary involvement in COVID-19 pneumonia by means of a cascade of two U-nets: training and assessment on multiple datasets using different annotation criteria.

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