An Overview of Latest Methods in Deep Learning for Automated Identification of COVID-19 Infection from Chest X-rays and CT-Scan Images

COVID-19 is a widely spread pandemic that crippled almost all countries and created a critical impact on the quality of human life. The outbreak was started in 2019, and during past years, the coronavirus has undergone various mutations and generated dangerous variants. The best path to control the spread of the coronavirus is with rapid testing and isolation. Among various tests, X-rays and CT-scan images captured from the chest and lungs attracted clinicians and researchers with high sensitivity. Many researchers have developed different automated methods for the identification of COVID-19. Among various automated methods, deep learning-based techniques obtained favourable results in the automation of COVID-19 detection. This paper proposes a detailed review of the latest deep learning methods that are utilized for COVID-19 identification from X-rays and CT scans. The recent publications are carefully choosed from the literature, and a detailed review is conducted. The literature search was conducted in various databases such as Google Scholar, PubMed, and Scopus. The proposed review will be helpful for future researchers in the area of COVID-19 research.