International Journal of Advance Computational Engineering and Networking (IJACEN)
.
Follow Us On :
current issues
Volume-10,Issue-4  ( Apr, 2022 )
Past issues
  1. Volume-10,Issue-3  ( Mar, 2022 )
  2. Volume-10,Issue-2  ( Feb, 2022 )
  3. Volume-10,Issue-1  ( Jan, 2022 )
  4. Volume-9,Issue-12  ( Dec, 2021 )
  5. Volume-9,Issue-11  ( Nov, 2021 )
  6. Volume-9,Issue-10  ( Oct, 2021 )
  7. Volume-9,Issue-9  ( Sep, 2021 )
  8. Volume-9,Issue-8  ( Aug, 2021 )
  9. Volume-9,Issue-7  ( Jul, 2021 )
  10. Volume-9,Issue-6  ( Jun, 2021 )

Statistics report
Jun. 2022
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 112
Paper Published : 1361
No. of Authors : 3438
  Journal Paper


Paper Title :
Chest X-Ray Based Covid 19 Patient Monitoring using Python

Author :Manisha Sahu, Kusum Sharma, Rahul Mishra

Article Citation :Manisha Sahu ,Kusum Sharma ,Rahul Mishra , (2021 ) " Chest X-Ray Based Covid 19 Patient Monitoring using Python " , International Journal of Advance Computational Engineering and Networking (IJACEN) , pp. 32-36, Volume-9,Issue-6

Abstract : The 2019 novel coronavirus disease (COVID-19), with a starting point in China, has spread rapidly among people living in other countries, and is approaching approximately 34,986,502 cases worldwide according to the statistics of European Centre for Disease Prevention and Control. There are a limited number of COVID-19 test kits available in hospitals due to the increasing cases daily. Therefore, it is necessary to implement an automatic detection system as a quick alternative diagnosis option to prevent COVID-19 spreading among people.Fusion was considered as a concatenation between the two individual vectors in this context. Speckle-affected and low-quality X-ray images along with good quality images were used in our experiment for conducting tests. If training and testing are performed with only selected good quality X-ray images in an ideal situation, the output accuracy may be found higher. However, this does not represent a reallife scenario, where the image database would be a mix of both good- and poor-quality images. Therefore, this approach of using different quality images would test how well the system can react to such real-life situations. A modified anisotropic diffusion filtering technique was employed to remove multiplicative speckle noise from the test images. The application of these techniques could effectively overcome the limitations in input image quality. Next, the feature extraction was carried out on the test images. Finally, the CNN classifier performed a classification of X-ray images to identify whether it was COVID-19 or not. Keywords - Chest X-Ray, Covid 19, Monitoring, Python, Confusion Matrix

Type : Research paper

Published : Volume-9,Issue-6


DOIONLINE NO - IJACEN-IRAJ-DOIONLINE-18048   View Here

Copyright: © Institute of Research and Journals

| PDF |
Viewed - 36
| Published on 2021-10-16
   
   
IRAJ Other Journals
IJACEN updates
Paper Submission is open now for upcoming Issue.
The Conference World

JOURNAL SUPPORTED BY