Fully automated unified prognosis of Covid-19 chest X-ray/CT scan images using Deep Covix-Net model.

ABSTRACT: SARS-COV2 (Covid-19) prevails in the form of multiple mutant variants causing pandemic situations around the world. Thus, medical diagnosis is not accurate. Although several clinical diagnostic methodologies have been introduced hitherto, chest X-ray and computed tomography (CT) imaging techniques complement the analytical methods (for instance, RT-PCR) to a certain extent. In this context, we demonstrate a novel framework by employing various image segmentation models to leverage the available image databases (9000 chest X-ray images and 6000 CT scan images). The proposed methodology is expected to assist in the prognosis of Covid-19-infected individuals through examination of chest X-rays and CT scans of images using the Deep Covix-Net model for identifying novel coronavirus-infected pat

SUBMITTER: Vinod DN 

PROVIDER: S-EPMC8330146 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature