Abstract

The COVID-19 pandemic has underscored the significance of radiology in the early detection and precise diagnosis of the disease. This research article presents a systematic exploration of various radiological modalities employed in the context of COVID-19, examining their efficacy, challenges, and emerging trends. From traditional chest imaging to cutting-edge artificial intelligence (AI) applications, this study aims to provide a comprehensive overview of the evolving landscape of radiological approaches during the ongoing global health crisis. According to the findings, deep learning-based models have an extraordinary capacity to offer an accurate and efficient system for the detection and diagnosis of COVID-19, the use of which in the processing of modalities would lead to a significant increase in sensitivity and specificity values.

The application of deep learning in the field of COVID-19 radiologic image processing reduces false-positive and negative errors in the detection and diagnosis of this disease and offers a unique opportunity to provide fast, cheap, and safe diagnostic services to patients.