Abstract:

The pandemic related to the COVID-19 is one of the deadly epidemics. To reduce the further spread of the disease the alternative testing methods based on artificial intelligence have been evaluated. The chest X-Ray images with viral bacterial pneumonia provide remarkable information about COVID-19. An artificial intelligence system can help radiologists to detect COVID-19 from these chest X-Ray images. Generative Adversarial Networks (GANs) are used in areas such as expanding the image dataset (image augmentation), obtaining high-resolution images, transferring a pattern from one image to another. In this paper, the current studies which detect COVID-19 from the chest X-Ray images have been comprehensively discussed. Moreover, the properties of the datasets used in these studies, generating synthetic images with GAN and transfer learning approaches have been emphasized. This paper aims to provide a comprehensive report for other studies which detect COVID-19 from the chest X-Ray images.

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