- Published
- 18 July 2024
- Conference item
Machine learning model based on Gray-level co-occurrence matrix for chest Sarcoidosis diagnosis
- Authors
- Source
- 2nd International Engineering Conference on Electrical, Energy, and Artificial Intelligence, EICEEAI 2023
Abstract
Sarcoidosis is often misdiagnosed and mistreated due to the limitations of radiological presentations. With the recent emergence of COVID-19, doctors face challenges distinguishing between the symptoms of these two diseases. As a result, people are adapting to new practices such as working from home, wearing masks, and using disinfectants. The similarity in symptoms between sarcoidosis and COVID-19 has made it difficult to differentiate between the two conditions, potentially impacting patient outcomes. The diagnostic process for distinguishing between them is time-consuming, labor-intensive, and costly. Researchers and medical practitioners have gained significant attention to computer-aided detection (CAD) systems for sarcoidosis using radiological images to address this issue. This study uses machine learning classifiers, ensembles, and features such as Gray-Level Co-occurrence Matrix (GLCM) and histogram analysis to identify lung sarcoidosis infection from chest X-ray images. The proposed method extracts statistical texture features from X-ray images by calculating a GLCM for each image using various stride combinations. These GLCM features are then used to train the machine learning classifiers and ensembles. The research focuses on multi-class classification, categorizing X-ray images into three classes: sarcoidosis-affected, COVID-19-affected, and regular lungs, as well as binary classification, distinguishing sarcoid-affected cases from others. The proposed method, known for its simplicity and computational efficiency, demonstrates significant accuracy in identifying sarcoidosis and COVID-19 from chest X-ray images.
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Cite as
Attar, H., Solyman, A., Deif, M., Hafez, M., Kasem, H. & Mohamed, A. 2024, 'Machine learning model based on Gray-level co-occurrence matrix for chest Sarcoidosis diagnosis', 2nd International Engineering Conference on Electrical, Energy, and Artificial Intelligence, EICEEAI 2023. https://doi.org/10.1109/EICEEAI60672.2023.10590168