Abstract
With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques. This research results showed that rapidly evolved Artificial Intelligence (AI) -based image analysis can accomplish high accuracy in detecting coronavirus infection as well as quantification and illness burden monitoring.
Keywords
COVID-19, Deep Learning, Image Processing, Neural Network, X-Ray Image Processing
Article Type
Article
How to Cite this Article
Zaki, Salim M.; Jaber, Mustafa Musa; and Kashmoola, Mohammed A.
(2022)
"Diagnosing COVID-19 Infection in Chest X-Ray Images Using Neural Network,"
Baghdad Science Journal: Vol. 19:
Iss.
6, Article 2.
DOI: https://doi.org/10.21123/bsj.2022.5965