SN Comput Sci . HOG + CNN Net: Diagnosing COVID-19 and Pneumonia by Deep Neural Network from Chest X-Ray Images

[tetano]

SN Comput Sci


. 2021;2(5):371.
doi: 10.1007/s42979-021-00762-x. Epub 2021 Jul 8.
HOG + CNN Net: Diagnosing COVID-19 and Pneumonia by Deep Neural Network from Chest X-Ray Images


Mohammad Marufur Rahman ¹ , Sheikh Nooruddin ¹ , K M Azharul Hasan ¹ , Nahin Kumar Dey ¹



Affiliations

• PMID: 34254055
• PMCID: PMC8264179
• DOI: 10.1007/s42979-021-00762-x

Abstract

Coronavirus disease 2019 in short COVID-19 is a contagious disease caused by coronavirus SARS-CoV-2, which has caused a global pandemic and still infecting millions around the globe. COVID-19 has made an enormous impact on everybody's day-to-day life. One of the main strengths of COVID-19 is its extraordinary infectious capability. Early detection systems can thus play a big role in curbing the exponential growth of COVID-19. Some medical radiography techniques, such as chest X-rays and chest CT scans, are used for fast and reliable detection of coronavirus-induced pneumonia. In this paper, we propose a histogram of oriented gradients and deep convolutional network-based model that can find out the specific abnormality in frontal chest X-ray images and effectively classify the data into COVID-19 positive, pneumonia positive, and normal classes. The proposed system performed effectively in terms of various performance measures and proved capable as an effective early detection system.

Keywords: COVID-19; Convolution Neural Network (CNN); Histogram-Oriented Gradients (HOG); Pneumonia; X-ray images.