Detection of Pneumonia in COVID-19 Patients Using X-ray Images

Year : 2023 | Volume :01 | Issue : 01 | Page : 13-23
By

    S.S. Kiran

  1. K Gurucharan

  2. M. Rajan Babu

  3. S. Durgamadhuri

  4. M. Swathi

  5. M. Sravanthi

  1. Assistant Professor, Lendi Institute of Engineering and Technology, Andhra Pradesh, India
  2. Assistant Professor, Lendi Institute of Engineering and Technology, Andhra Pradesh, India
  3. Professor, Lendi Institute of Engineering and Technology, Andhra Pradesh, India
  4. Assistant Professor, Lendi Institute of Engineering and Technology, Andhra Pradesh, India
  5. Student, Lendi Institute of Engineering and Technology, Andhra Pradesh, India
  6. Student, Trainee Software Engineer, Prolifics, Telangana, India

Abstract

This study explores the use of chest X-ray image analysis and deep learning methods to identify pneumonia in COVID-19 patients. Due to the pandemic, Proper as well as immediate examination of COVID-19 is now essential for patient care and disease control. This study proposes a novel approach that uses convolutional neural networks (CNNs) to automatically predict pneumonia in COVID-19 patients using chest X-ray images. In this study, an X-ray of the chest that have been categorized are one-hot encoded using machine learning techniques like LabelBinarizer and then converted into emphatic form applying the categorical functionality of Python. Following that, a method for identification is created utilizing a range of the deep learning features, including convolutional neural network (CNN), VGG16, average pooling 2D (AP2D), dropout, flatten, dense, and input. The proposed approach was evaluated on a 5000 chest X-ray images in the dataset, obtaining excellent classification accuracy of 94%, sensitivity of 60%, and specificity of 100% for healthy and infections with pneumonia. The results demonstrate The possibility of using deep learning methods with accurately and quickly identify pneumonia in COVID-19 patients, which can enhance the health of patients and contribute to preventing the disease’s spread. The method carefully reduces training loss while also improving accuracy.

Keywords: COVID-19, SARS-CoV-2, Pneumonia, CNN, One hot encoding, Deep Learning, X-Ray, Bacteria, Viruses, Medical imaging.

[This article belongs to International Journal of Radio Frequency Innovations(ijrfi)]

How to cite this article: S.S. Kiran, K Gurucharan, M. Rajan Babu, S. Durgamadhuri, M. Swathi, M. Sravanthi.Detection of Pneumonia in COVID-19 Patients Using X-ray Images.International Journal of Radio Frequency Innovations.2023; 01(01):13-23.
How to cite this URL: S.S. Kiran, K Gurucharan, M. Rajan Babu, S. Durgamadhuri, M. Swathi, M. Sravanthi , Detection of Pneumonia in COVID-19 Patients Using X-ray Images ijrfi 2023 {cited 2023 Nov 17};01:13-23. Available from: https://journals.stmjournals.com/ijrfi/article=2023/view=126464


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Regular Issue Subscription Original Research
Volume 01
Issue 01
Received September 8, 2023
Accepted September 22, 2023
Published November 17, 2023
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