A comprehensive survey on Covid-19 disease diagnosis: Datasets, deep learning approaches and challenges

Abstract

Millions of people were affected by the global health disaster brought on by the coronavirus (Covid-19) pandemic in December 2019, severely impacting the international economy. Deep learning (DL) methods successfully analyzed and detected infectious areas in radiological images. This research analyses the Covid-19 open-source datasets and Deep Learning methodologies and develops a categorization based on diagnostic approaches and learning methodologies at most using X-ray and CT imaging. Coronavirus diagnosis at image and region level analysis is systematically divided into classification, segmentation, and multi-stage procedures. Furthermore, a discussion of the significant obstacles and potential future research directions is included.

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