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COVIDetection-Net: A tailored COVID-19 detection from chest radiography images using deep learning
Ahmed S Elkorany1,2, Zeinab F Elsharkawy3
1Dept. of Electronics and Electrical Comm. Eng., Faculty of Electronic Engineering, Menouf, 32952, Menoufia University, Egypt.
Optik
|February 8, 2021
Summary
A new Deep Learning system, COVIDetection-Net, accurately detects COVID-19 from chest X-rays. This AI tool offers a vital solution for rapid COVID-19 diagnosis, especially where testing kits are scarce.
Area of Science:
- Medical Imaging
- Artificial Intelligence
- Infectious Disease Diagnostics
Background:
- The COVID-19 pandemic highlighted the need for rapid and accurate diagnostic tools.
- Chest radiography images (CRIs) are a common resource for diagnosing respiratory illnesses, including COVID-19.
- Existing diagnostic methods may face limitations in speed and accessibility.
Purpose of the Study:
- To propose and evaluate a Deep Learning (DL) based medical system, named COVIDetection-Net, for the automatic detection of COVID-19 infection.
- To assess the system's performance in classifying various respiratory conditions using CRIs.
- To provide an efficient diagnostic aid in resource-limited settings during the COVID-19 pandemic.
Main Methods:
- Development of COVIDetection-Net, a DL system integrating ShuffleNet and SqueezeNet architectures for feature extraction.
- Utilizing Multiclass Support Vector Machines (MSVM) for classification of CRIs.
- Dataset comprised of 1200 CRIs from two publicly available databases.
- Performance evaluation using metrics such as accuracy, recall, specificity, precision, F1-Score, Confusion Matrix (CM), and Receiver Operation Characteristics (ROC) analysis.
Main Results:
- Achieved 100% accuracy for COVID/NonCOVID classification.
- Obtained 99.72% accuracy for COVID/Normal/pneumonia classification.
- Reached 94.44% accuracy for COVID/Normal/Bacterial pneumonia/Viral pneumonia classification.
- Demonstrated superior performance compared to existing methods across multiple evaluation metrics.
Conclusions:
- COVIDetection-Net is a highly accurate and efficient AI system for detecting COVID-19 from CRIs.
- The system shows significant potential as a diagnostic tool, particularly in areas with limited access to testing kits.
- The proposed model offers a valuable contribution to managing the ongoing COVID-19 pandemic.
