  Analysis of chest CT scans can be used in detecting parts of lungs that are
affected by infectious diseases such as COVID-19.Determining the volume of
lungs affected by lesions is essential for formulating treatment
recommendations and prioritizingpatients by severity of the disease. In this
paper we adopted an approach based on using an ensemble of deep
convolutionalneural networks for segmentation of slices of lung CT scans. Using
our models we are able to segment the lesions, evaluatepatients dynamics,
estimate relative volume of lungs affected by lesions and evaluate the lung
damage stage. Our modelswere trained on data from different medical centers. We
compared predictions of our models with those of six experiencedradiologists
and our segmentation model outperformed most of them. On the task of
classification of disease severity, ourmodel outperformed all the radiologists.
