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Detection of COVID-19 Using VGG-16 Neural Network and Classification of Chest X-ray Images
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Nader Jafarnia Dabanloo    , Seyed Mohammad Javad Hosseini * , Keivan Maghooli |
| Department of Biomedical Engineering, Islamic Azad University, E-Campus, Tehran, Iran , javadhosseini1377@yahoo.com |
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Abstract: (1998 Views) |
Background and Aim: With the increase in the number of infections and deaths of covid-19, the need is felt to use artificial intelligence and machine learning tools to diagnose the corona virus quickly and on time. In this study, using chest x-ray images and VGG-16 deep neural network, an automatic system was designed and implemented to detect cases of covid-19.
Methods: In this research, chest x-ray images obtained from the Kaggle database were used. The design of this study included: data sampling, training division, creating directories, transferring images to their own folders, classifying images, creating the proposed VGG-16 model in Python programming language and Keras and Tensorflow libraries, evaluation of the proposed model and finally the creation of the confusion matrix and their analysis and interpretation.
Results: The accuracy and Precision of the proposed model for the positive Covid-19 class were 91 and 93%, respectively. Also, the recall rate and F1-Score for cases with covid-19 were 94% and 88% respectively.
Conclusion: Due to the high accuracy and precision of the proposed model, it can be used to diagnose covid-19 and separate COVID-19 cases from healthy cases and also be used as an auxiliary tool to help doctors diagnose this disease. |
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| Keywords: COVID-19, corona virus, detecting of COVID-19, X-ray images, chest, deep learning |
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Full-Text [PDF 801 kb]
(721 Downloads)
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Type of Study: Original Article |
Subject:
Marine Medicine
Received: 2023/02/5 | Accepted: 2024/02/17 | Published: 2024/05/30
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