期刊
出版社
IEEE
DOI: 10.1109/SACVLC53127.2021.9652248
关键词
Artificial Neural Network (ANN); COVID-19; Support Vector Machine (SVM); Pneumonia; X-rays
资金
- FONDEF [ID21I10191]
- FONDECYT [1211132, 1200810]
- UCM
- [Dicyt062117S]
This article discusses the implementation of algorithms for automatic diagnosis of lung diseases such as COVID-19 and Pneumonia from chest X-rays, achieving a maximum accuracy of 93.73% for SVM classifier.
Due to the coronavirus pandemic and the lack of an automatic COVID-19 diagnostic system to relieve congestion in health centers and to support the traceability of this disease, this article exposes the implementation of algorithms for automatic diagnosis of lung diseases such as COVID-19 and Pneumonia from chest X-rays (CXR) through GLCM and HOG features extraction using 6300 patches. Then, selecting the best features and different classifiers such as an Support Vector Machine (SVM) and Artificial Neural Network (ANN) to obtain a system maximum accuracy of 93,73% for SVM.
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