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COVID-19 chest X-ray image analysis by threshold-based segmentation

COVID-19 is a severe acute respiratory syndrome that has caused a major ongoing pandemic worldwide. Imaging systems such as conventional chest X-ray (CXR) and computed tomography (CT) were proven essential for patients due to the lack of information about the complications that could result from thi...

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Autores principales: Al-Zyoud, Walid, Erekat, Dana, Saraiji, Rama
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9998128/
https://www.ncbi.nlm.nih.gov/pubmed/36919086
http://dx.doi.org/10.1016/j.heliyon.2023.e14453
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author Al-Zyoud, Walid
Erekat, Dana
Saraiji, Rama
author_facet Al-Zyoud, Walid
Erekat, Dana
Saraiji, Rama
author_sort Al-Zyoud, Walid
collection PubMed
description COVID-19 is a severe acute respiratory syndrome that has caused a major ongoing pandemic worldwide. Imaging systems such as conventional chest X-ray (CXR) and computed tomography (CT) were proven essential for patients due to the lack of information about the complications that could result from this disease. In this study, the aim was to develop and evaluate a method for automatic diagnosis of COVID-19 using binary segmentation of chest X-ray images. The study used frontal chest X-ray images of 27 infected and 19 uninfected individuals from Kaggle COVID-19 Radiography Database, and applied binary segmentation and quartering in MATLAB to analyze the images. The binary images of the lung were split into four quarters; Q1 = right upper quarter, Q2 = left upper quarter, Q3 = right lower, and Q4 = left lower. The results showed that COVID-19 patients had a higher percentage of attenuation in the lower lobes of the lungs (p-value < 0.00001) compared to healthy individuals, which is likely due to ground-glass opacities and consolidations caused by the infection. The ratios of white pixels in the four quarters of the X-ray images were calculated, and it was found that the left lower quarter had the highest number of white pixels but without a statistical significance compared to right lower quarter (p-value = 0.102792). This supports the theory that COVID-19 primarily affects the lower and lateral fields of the lungs, and suggests that the virus is accumulated mostly in the lower left quarter of the lungs. Overall, this study contributes to the understanding of the impact of COVID-19 on the respiratory system and can help in the development of accurate diagnostic methods.
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spelling pubmed-99981282023-03-10 COVID-19 chest X-ray image analysis by threshold-based segmentation Al-Zyoud, Walid Erekat, Dana Saraiji, Rama Heliyon Research Article COVID-19 is a severe acute respiratory syndrome that has caused a major ongoing pandemic worldwide. Imaging systems such as conventional chest X-ray (CXR) and computed tomography (CT) were proven essential for patients due to the lack of information about the complications that could result from this disease. In this study, the aim was to develop and evaluate a method for automatic diagnosis of COVID-19 using binary segmentation of chest X-ray images. The study used frontal chest X-ray images of 27 infected and 19 uninfected individuals from Kaggle COVID-19 Radiography Database, and applied binary segmentation and quartering in MATLAB to analyze the images. The binary images of the lung were split into four quarters; Q1 = right upper quarter, Q2 = left upper quarter, Q3 = right lower, and Q4 = left lower. The results showed that COVID-19 patients had a higher percentage of attenuation in the lower lobes of the lungs (p-value < 0.00001) compared to healthy individuals, which is likely due to ground-glass opacities and consolidations caused by the infection. The ratios of white pixels in the four quarters of the X-ray images were calculated, and it was found that the left lower quarter had the highest number of white pixels but without a statistical significance compared to right lower quarter (p-value = 0.102792). This supports the theory that COVID-19 primarily affects the lower and lateral fields of the lungs, and suggests that the virus is accumulated mostly in the lower left quarter of the lungs. Overall, this study contributes to the understanding of the impact of COVID-19 on the respiratory system and can help in the development of accurate diagnostic methods. Elsevier 2023-03-10 /pmc/articles/PMC9998128/ /pubmed/36919086 http://dx.doi.org/10.1016/j.heliyon.2023.e14453 Text en © 2023 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Al-Zyoud, Walid
Erekat, Dana
Saraiji, Rama
COVID-19 chest X-ray image analysis by threshold-based segmentation
title COVID-19 chest X-ray image analysis by threshold-based segmentation
title_full COVID-19 chest X-ray image analysis by threshold-based segmentation
title_fullStr COVID-19 chest X-ray image analysis by threshold-based segmentation
title_full_unstemmed COVID-19 chest X-ray image analysis by threshold-based segmentation
title_short COVID-19 chest X-ray image analysis by threshold-based segmentation
title_sort covid-19 chest x-ray image analysis by threshold-based segmentation
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9998128/
https://www.ncbi.nlm.nih.gov/pubmed/36919086
http://dx.doi.org/10.1016/j.heliyon.2023.e14453
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