Abstract
Covid-19 is a type of pneumonia disease currently affecting people around the world. Covid-19 and tuberculosis are lung diseases that are dangerous and spread quickly to other humans. Chest radiography is one of the main modalities in the management of suspected COVID-19 and tuberculosis patients as it provides radiological information on lung infections that can be used as diagnostic guidelines and patient care. This study aims to determine the differences in optical density and contrast in Covid-19 and pneumonia tuberculosis cases in order to find the specific characteristics of Covid-19 and tuberculosis. This research processed secondary data from Covid-19 and tuberculosis positive patients using image-J software that can be easily obtained and operated by anyone. After processing, the density and contrast were analyzed, particularly for the lungs. Based on image processing results, the average density for Cnovid-19 radiographs is 1,066, while for Tuberculosis radiograph is 1,519. The average contrast values for Covid-19 and tuberculosis radiographs are 0.37 and 1.03. Thus, it can be concluded that the contrast of the Covid-19 radiograph is lower than the tuberculosis radiograph. The difference in optical density on the tuberculosis and Covid-19 cases is 0.5 as the opacity on the chest radiographs of Covid-19 patients is evenly distributed over the entire lung surface.
Publisher
Trans Tech Publications, Ltd.
Subject
Anesthesiology and Pain Medicine
Reference33 articles.
1. COVID-19 pneumonia: pathophysiology and management;Gattinoni;European Respiratory Review,2021
2. COVID-19 pneumonia: A review of typical CT findings and differential diagnosis;Hani;Diagnostic and Interventional Imaging
3. Ardan, M., Rahman, F. F., & Geroda, G. B. (2020). The influence of physical distance to student anxiety on COVID-19, Indonesia. Journal of Critical Reviews, 7(17), 1126-1132.
4. Review and analysis of current responses to COVID-19 in Indonesia: Period of January to March 2020;Djalante;Progress in Disaster Science
5. Online learning sentiment analysis during the covid-19 Indonesia pandemic using twitter data;Sahir;IOP Conference Series: Materials Science and Engineering