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Reseach Article

Predicting COVID-19 Pneumonia Severity based on Chest X-ray with Deep Learning

by Swati Shekapure, Nikita Pagar, Bhagyashree Kulkarni, Dinesh Choudhary, Priti Parkhad
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 183 - Number 7
Year of Publication: 2021
Authors: Swati Shekapure, Nikita Pagar, Bhagyashree Kulkarni, Dinesh Choudhary, Priti Parkhad
10.5120/ijca2021921353

Swati Shekapure, Nikita Pagar, Bhagyashree Kulkarni, Dinesh Choudhary, Priti Parkhad . Predicting COVID-19 Pneumonia Severity based on Chest X-ray with Deep Learning. International Journal of Computer Applications. 183, 7 ( Jun 2021), 9-11. DOI=10.5120/ijca2021921353

@article{ 10.5120/ijca2021921353,
author = { Swati Shekapure, Nikita Pagar, Bhagyashree Kulkarni, Dinesh Choudhary, Priti Parkhad },
title = { Predicting COVID-19 Pneumonia Severity based on Chest X-ray with Deep Learning },
journal = { International Journal of Computer Applications },
issue_date = { Jun 2021 },
volume = { 183 },
number = { 7 },
month = { Jun },
year = { 2021 },
issn = { 0975-8887 },
pages = { 9-11 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume183/number7/31937-2021921353/ },
doi = { 10.5120/ijca2021921353 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:16:06.341776+05:30
%A Swati Shekapure
%A Nikita Pagar
%A Bhagyashree Kulkarni
%A Dinesh Choudhary
%A Priti Parkhad
%T Predicting COVID-19 Pneumonia Severity based on Chest X-ray with Deep Learning
%J International Journal of Computer Applications
%@ 0975-8887
%V 183
%N 7
%P 9-11
%D 2021
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Pneumonia is an infectious disease that affects one or both lungs in the human body commonly caused by bacteria called Streptococcus pneumonia. It is an infection of microscopic particles in the air sacs of the lungs, called alveoli. Chest X-Rays are used to diagnose pneumonia and which needs an expert radiotherapist for evaluation. This may vary over time from practitioner to practitioner. This is based upon the person’s experience too. Therefore, an automated system is required that can help patients to diagnose pneumonia without any of these constraints. We propose an image-based automated system that detects pneumonia diseases using Artificial intelligence. The system will be making the use of computational techniques for analyzing, processing, and classifying the image data predicated upon various features of the images. Unwanted noise is filtered and the resulting image is processed for enhancing the image. Complex techniques are used for feature extraction like the Convolutional Neural Network (CNN) followed by classifying images based upon various algorithms. The diagnosis report is generated as an output that also contains a severity score. This system will generate more precise results and will provide them faster than the traditional method, making this application more efficient and dependable. This application can also be used as a real-time teaching tool for medical students in the radiology domain.

References
  1. Xiaosong Wang, Yifan Peng, Le Lu, Zhiyong Lu, Mohammadhadi Bagheri and Ronald M Summers, ”Chestx-ray8: Hospital-scale chest x-ray database and benchmarks on weakly-supervised classification and localization of common thorax diseases”, Computer Vision and Pattern Recognition (CVPR) 2017 IEEE Conference on, pp.34623471, 2017.
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  4. Ai T, Yang Z, Hou H, Zhan C, Chen C, Lv W, et al. Correlation of Chest CT and RT-PCR Testing in Coronavirus Disease 2019 (COVID-19) in China: A Report of 1014 Cases. Radiology 2020 Feb 26:200642 [FREE Full text] [CrossRef] [Medline].
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Index Terms

Computer Science
Information Sciences

Keywords

Image Processing Artificial Intelligence(AI) Neural Network Deep Learning COVID-19 Viral pneumonia.