A review of intelligent medical imaging diagnosis for the COVID-19 infection

Abstract

Due to the unavailability of specific vaccines or drugs to treat COVID-19 infection, the world has witnessed a rise in the human mortality rate. Currently, real time RT-PCR technique is widely accepted to detect the presence of the virus, but it is time consuming and has a high rate of eliciting false positives/negatives results. This has opened research avenues to identify substitute strategies to diagnose the infection. Related works in this direction have shown promising results when RT-PCR diagnosis is complemented with Chest imaging results. Finally integrating intelligence and automating diagnostic systems can improve the speed and efficiency of the diagnosis process which is extremely essential in the present scenario. This paper reviews the use of CT scan, Chest X-ray, lung ultrasound images for COVID-19 diagnosis, discusses the automation of chest image analysis using machine learning and deep learning models, elucidates the achievements, challenges, and future directions in this domain.