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In this paper, we present a hybrid deep learning framework named CTNet whichcombines convolutional neural network and transformer together for thedetection of COVID-19 via 3D chest CT images. It consists of a CNN featureextractor module with SE attention to extract sufficient features from CTscans, together with a transformer model to model the discriminative featuresof the 3D CT scans. Compared to previous works, CTNet provides an effective andefficient method to perform COVID-19 diagnosis via 3D CT scans with dataresampling strategy. Advanced results on a large and public benchmarks,COV19-CT-DB database was achieved by the proposed CTNet, over thestate-of-the-art baseline approachproposed together with the dataset.

A hybrid deep learning framework for Covid-19 detection via 3D Chest CT Images