Preliminary Stages for COVID-19 Detection Using Image Processing

COVID-19 was first discovered in December 2019 in Wuhan. There have been reports of thousands of illnesses and hundreds of deaths in almost every region of the world. Medical images, when combined with cutting-edge technology such as artificial intelligence, have the potential to improve the efficiency of the public health system and deliver faster and more reliable findings in the detection of COVID-19. The process of developing the COVID-19 diagnostic system begins with image accusation and proceeds via preprocessing, feature extraction, and classification. According to literature review, several attempts to develop taxonomies for COVID-19 detection using image processing methods have been introduced. However, most of these adhere to a standard category that exclusively considers classification methods. Therefore, in this study a new taxonomy for the early stages of COVID-19 detection is proposed. It attempts to offer a full grasp of image processing in COVID-19 while considering all phases required prior to classification. The survey concludes with a discussion of outstanding concerns and future directions.

Automated summary

COVID-19 was first discovered in Wuhan in December 2019 and has since affected every region in the world, causing thousands of illnesses and hundreds of deaths. The combination of medical imaging and artificial intelligence has the potential to enhance the efficiency of the public health system and provide faster and more reliable detection of COVID-19. This study proposes a new taxonomy for the early stages of COVID-19 detection, taking into account all phases prior to classification.