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Automated Covid-19 Detection System with CNN using Chest X-Ray and CT-Scans

Bibek Ranjan Ghosh1 , Siddhartha Banerjee2 , Ayush Nandi3 , Arya Panja4 , Pritam Mondal5 , Arunava Das6

Section:Review Paper, Product Type: Journal Paper
Volume-10 , Issue-5 , Page no. 47-52, May-2022

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v10i5.4752

Online published on May 31, 2022

Copyright © Bibek Ranjan Ghosh, Siddhartha Banerjee, Ayush Nandi, Arya Panja, Pritam Mondal, Arunava Das . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Bibek Ranjan Ghosh, Siddhartha Banerjee, Ayush Nandi, Arya Panja, Pritam Mondal, Arunava Das, “Automated Covid-19 Detection System with CNN using Chest X-Ray and CT-Scans,” International Journal of Computer Sciences and Engineering, Vol.10, Issue.5, pp.47-52, 2022.

MLA Style Citation: Bibek Ranjan Ghosh, Siddhartha Banerjee, Ayush Nandi, Arya Panja, Pritam Mondal, Arunava Das "Automated Covid-19 Detection System with CNN using Chest X-Ray and CT-Scans." International Journal of Computer Sciences and Engineering 10.5 (2022): 47-52.

APA Style Citation: Bibek Ranjan Ghosh, Siddhartha Banerjee, Ayush Nandi, Arya Panja, Pritam Mondal, Arunava Das, (2022). Automated Covid-19 Detection System with CNN using Chest X-Ray and CT-Scans. International Journal of Computer Sciences and Engineering, 10(5), 47-52.

BibTex Style Citation:
@article{Ghosh_2022,
author = {Bibek Ranjan Ghosh, Siddhartha Banerjee, Ayush Nandi, Arya Panja, Pritam Mondal, Arunava Das},
title = {Automated Covid-19 Detection System with CNN using Chest X-Ray and CT-Scans},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2022},
volume = {10},
Issue = {5},
month = {5},
year = {2022},
issn = {2347-2693},
pages = {47-52},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=5467},
doi = {https://doi.org/10.26438/ijcse/v10i5.4752}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v10i5.4752}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=5467
TI - Automated Covid-19 Detection System with CNN using Chest X-Ray and CT-Scans
T2 - International Journal of Computer Sciences and Engineering
AU - Bibek Ranjan Ghosh, Siddhartha Banerjee, Ayush Nandi, Arya Panja, Pritam Mondal, Arunava Das
PY - 2022
DA - 2022/05/31
PB - IJCSE, Indore, INDIA
SP - 47-52
IS - 5
VL - 10
SN - 2347-2693
ER -

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Abstract

: Covid19 is the menace of this century. World Health Organization (WHO) declared it pandemic in February, 2020. This RNA virus has catastrophic impact of the entire human civilization since it was initially reported to have been erupted from Wuhan, a city in Hubei province of China in late December 2019. In the first wave millions of people died in many countries. Even the developed countries like USA, France, Italy, United Kingdom etc. were in shock and could not prevent loss of human lives with their well-established medical infrastructure. Strict lockdown, quarantines were imposed. The hospitals were outnumbered by the severely ill patients who needed ventilation support. Many died without treatment, dead bodies were on the streets and mass graves became a practice. Developing and under-developed countries faced even more disastrous situations. Since then the virus is mutating and giving new challenges to human society in developing a cure. Until now RTPCR and other test are carried out to detect the disease. But they take somewhat longer time. So researchers are using artificial intelligence based techniques especially deep learning methods to develop new models using the CT scans (CTS) and chest X-ray (CXR) images of the patients to detect the disease in real time. This work focuses on the methods developed so far for detecting Covid-19 using convolutional neural network and compare their performances.

Key-Words / Index Term

Covid-19, CT scan, Pneumonia, Chest X-ray, CNN.

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