Abstract
COVID-19 declared as a pandemic that has a faster rate of infection and has impacted the lives and the country’s economy due to forced lockdowns. Its detection using RT-PCR is required long time and due to which its infection has grown exponentially. This creates havoc for the shortage of testing kits in many countries. This work has proposed a new image processing-based technique for the health care systems named “C19D-Net”, to detect “COVID-19” infection from “Chest X-Ray” (XR) images, which can help radiologists to improve their accuracy of detection COVID-19. The proposed system extracts deep learning (DL) features by applying the InceptionV4 architecture and Multiclass SVM classifier to classify and detect COVID-19 infection into four different classes. The dataset of 1900 Chest XR images has been collected from two publicly accessible databases. Images are pre-processed with proper scaling and regular feeding to the proposed model for accuracy attainments. Extensive tests are conducted with the proposed model (“C19D-Net”) and it has succeeded to achieve the highest COVID-19 detection accuracy as 96.24% for 4-classes, 95.51% for three-classes, and 98.1% for two-classes. The proposed method has outperformed well in expressions of “precision”, “accuracy”, “F1-score” and “recall” in comparison with most of the recent previously published methods. As a result, for the present situation of COVID-19, the proposed “C19D-Net” can be employed in places where test kits are in short supply, to help the radiologists to improve their accuracy of detection of COVID-19 patients through XR-Images.
Highlights
In 2019, a new virus known as COVID-19 emerged, which was caused by a coronavirus strain known as “SARS-CoV-2”
Each time the C19D-Net proposed model
A deep learning C19D-Net model is proposed for exploiting chest XR images to detect and classify
Summary
In 2019, a new virus known as COVID-19 emerged, which was caused by a coronavirus strain known as “SARS-CoV-2”. When the WHO labeled the COVID-19 outbreak a pandemic in March 2020, the situation became a worldwide health crisis. COVID-19 is a worldwide health emergency that resulted in over 45 million recorded illnesses and a death rate of 1.2 million, and the majority of the world is still in danger [1]. Prognostic forecasts are a prerequisite to enhance and coordinate the care of a patient during the COVID-19 pandemic. The COVID-19 makes antibiotics ineffective in treating patients, complicating the infection if their immune system is poor [2]. Several pharmaceutical corporations and research institutions have developed vaccines, and many countries commence vaccination; the hope that this pandemic could be defeated has
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More From: International Journal of Environmental Research and Public Health
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