With the outbreak of COVID-19, a large number of relevant studies have emerged in recent years. We propose an automatic COVID-19 diagnosis framework based on lung CT scan images, the PVT-COV19D. In order to accommodate the different dimensions of the image input, we first classified the images using Transformer models, then sampled the images in the dataset according to normal distribution, and fed the sampling results into the modified PVTv2 model for training. A large number of experiments on the COV19-CT-DB dataset demonstrate the effectiveness of the proposed method.
@article{arxiv.2206.15069,
title = {PVT-COV19D: Pyramid Vision Transformer for COVID-19 Diagnosis},
author = {Lilang Zheng and Jiaxuan Fang and Xiaorun Tang and Hanzhang Li and Jiaxin Fan and Tianyi Wang and Rui Zhou and Zhaoyan Yan},
journal= {arXiv preprint arXiv:2206.15069},
year = {2022}
}