  Early and reliable COVID-19 diagnosis based on chest 3-D CT scans can assist
medical specialists in vital circumstances. Deep learning methodologies
constitute a main approach for chest CT scan analysis and disease prediction.
However, large annotated databases are necessary for developing deep learning
models that are able to provide COVID-19 diagnosis across various medical
environments in different countries. Due to privacy issues, publicly available
COVID-19 CT datasets are highly difficult to obtain, which hinders the research
and development of AI-enabled diagnosis methods of COVID-19 based on CT scans.
In this paper we present the COV19-CT-DB database which is annotated for
COVID-19, consisting of about 5,000 3-D CT scans, We have split the database in
training, validation and test datasets. The former two datasets can be used for
training and validation of machine learning models, while the latter will be
used for evaluation of the developed models. We also present a deep learning
approach, based on a CNN-RNN network and report its performance on the
COVID19-CT-DB database.
