A Covid-19 Medical Image Classification Algorithm Based On Transformer

This paper proposes a novel deep learning network based on ResNet-50 merged transformer named RMT-Net for the automatic classification of coronavirus ID-19 lesions in clinical settings. The RMT-Net includes four stage blocks to realize the feature extraction of different receptive fields and a global average pooling layer and a fully connected layer perform classification tasks. The experimental results show that the RMT-Net model has a Test_ acc of 97.65% on the X-ray image dataset, 99.12% on the CT image dataset, which both higher than the other four models. The size of RMT-Net model is only 38.5 M, and the detection speed of X-ray image and CT image is 5.46 ms and 4.12 ms per image, respectively.