Enhancing CORONAVIRUS-19 Disease Diagnosis from CT Scans of Lung: Comparative Analysis Using Deep Learning Models and Edge Detection Techniques

The uncertainty of COVID-19 pandemics has underscored the need for accurate and timely diagnosis through chest CT scans. Diagnosing COVID-19 can be challenging due to potential confusion with other lung conditions. Researchers have used deep learning models to address this issue. This study compares these models and introduces a novel approach that utilizes edge detection techniques to enhance accuracy in COVID-19 diagnosis from lung CT scans. The research assesses the performance of various edge detection methods to identify the most effective technique for COVID-19 diagnosis. The proposed approach shows promising results, hinting at its potential in future COVID-19 outbreaks. This study sheds light on the use of deep learning and edge detection for COVID-19 diagnosis, suggesting areas for further research in the field.