  The outbreak of the novel coronavirus, officially declared a global pandemic,
has a severe impact on our daily lives. As of this writing there are
approximately 197,188 confirmed cases of which 80,881 are in "Mainland China"
with 7,949 deaths, a mortality rate of 3.4%. In order to support radiologists
in this overwhelming challenge, we develop a deep learning based algorithm that
can detect, localize and quantify severity of COVID-19 manifestation from chest
CT scans. The algorithm is comprised of a pipeline of image processing
algorithms which includes lung segmentation, 2D slice classification and fine
grain localization. In order to further understand the manifestations of the
disease, we perform unsupervised clustering of abnormal slices. We present our
results on a dataset comprised of 110 confirmed COVID-19 patients from Zhejiang
province, China.
