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.
翻译:随着COVID-19的爆发,近年来出现了大量相关研究,我们提议基于肺部CT扫描图像(PVT-COV19D)的自动COVID-19诊断框架。为了容纳图像输入的不同层面,我们首先使用变换模型对图像进行分类,然后根据正常分布在数据集中对图像进行抽样,并将取样结果输入经修改的PVTv2培训模型。关于COV19-CT-DB数据集的大量实验显示了拟议方法的有效性。