Abstract
Lung X-ray images, if processed using statistical and computational methods, can distinguish pneumonia from COVID-19. The present work shows that it is possible to extract lung X-ray characteristics to improve the methods of examining and diagnosing patients with suspected COVID-19, distinguishing them from malaria, tuberculosis, and Streptococcus pneumonia. More precisely, an intelligent computational model was developed to process lung X-ray images and classify whether the image is of a patient with COVID-19. In partnership with the municipality of Itapeva, Minas Gerais, we carried out patient analysis and, at the same time, we evolved the algorithms to meet the needs of health professionals and also expand support in tracking COVID-19 in the municipality. In this project we will describe cases and even signs and symptoms that were similar to the clinical performed by the doctor. The average recognition accuracy of COVID-19 was 0.97,4 ± 0.043.
Highlights
In November 2019, the first cases of COVID-19 were detected by China's health authorities
Before analyzing the 3800 chest X-ray images, we separated the left lung from the right using Mask-RCNN, as described in the methodology, and each segmented lung pair was labeled as type 1 pneumonia, type 2 pneumonia, or type 3 pneumonia (Table 2), based on the data set information and on the literature review on signs and symptoms
Haralick's texture descriptors were useful for efficiently representing patterns of interest for image analysis and interpretation, as they showed changes in pixel intensity patterns, which were correlating with pathological changes in COVID-19
Summary
In November 2019, the first cases of COVID-19 were detected by China's health authorities. The Ministry of Health recognized the occurrence of community transmission, from person to person, in the country - a late recognition, since there were already deaths unrelated to the transmission chains involving travelers [1]. In this context, one of the first steps towards adopting measures of social isolation and hospitalizations is to know who has been contaminated by COVID-19. The most appropriate tests for COVID-19 are molecular tests, but they can take 24 to 48 hours to be performing In pandemic conditions, this period can last between 5 and 10 days due to many requests, lack of equipment, and health professionals' help. As X-Ray and lung tomography tests indicate patients with respiratory problems, these tests may answer this demand
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