Identification of COVID-19 with Chest X-ray images using Deep learning
##plugins.themes.academic_pro.article.main##
Abstract
Covid-19 had become an outbreak at the end of December 2019, it has become a nightmare for all. It resulted in
a huge loss in the health, life and economic sector of a country. It is a common spreading disease. Its symptoms
are similar to pneumonia, which make it very hard to distinguish. After a clinical study of COVID-19 infected
patients, it is discovered that infected patients tend to have a lung infection after getting in contact with the virus.
Chest X-ray and CT scans are the most widely used techniques for detecting lung related problems. As many
countries are economically deprived after this situation, Chest X-ray is opted over CT scan, as the X-ray is less
expensive, fast and simple than CT scans. In the health sector, deep learning has always been a very effective
technique. Numerous sources of medical images help deep learning to improvise itself and help this technique
to combat COVID-19 outbreak. In this paper, we have described the dataset and model formulation. Then we
provided the comparison and analysis of models those we have used for the experimentation purpose. It describes
the implementation of each model and their comparison on the basis of loss and accuracy. Finally, we have
mentioned the results and discussion along with the future scopes that we hope to cover later on.
##plugins.themes.academic_pro.article.details##
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
- A.Abbas, M. a. Classification of covid-19 in chest x-ray images using detrac deep convolutional neural network. Springer Applied Intelligence 51, 854–864. DOI: https://doi.org/10.1007/s10489-020-01829-7
- A.Bansal, A. A. novel coronavirus (covid-19) diagnosis using computer vision and artificial intelligence techniques: a review. Multimed Tools Appl 80, 19931–19946. DOI: https://doi.org/10.1007/s11042-021-10714-5
- A.Moutaz, V., Alhyari, A., andAjith, A., and Jatana2020. Covid-19 prediction and detection
- using deep learning. Information Systems and Industrial Management Applications 12, 168–181.
- J.Gua, Z. Wangb,j.kuenb,l.mab,t.liub and n.aslam 2017. recent advances in convolutional neural networks. arXiv:1512.07108.
- Kim, D.-H. and Lee, H.-Y. Image manipulation detection using convolutional neural network. International Journal of Applied Engineering Research 12, 11640–11646.
- MXin and YWang. Research on image classification model based on deep convolution neural network. Eurasip Image Video Processing 40.
- O.Tulin, M. and andR.Acharya2020, E. Automated detection of covid-19 cases using deep neural networks with x-ray images. Information Systems and Industrial Management Applications 28.
- S.Bhattacharya, M., PPham, and SKrishnan. Deep learning and medical image processing for coronavirus (covid-19) pandemic: A survey. Sustainable Cities and Society 65. DOI: https://doi.org/10.1016/j.scs.2020.102589
- STammina. Transfer learning using vgg-16 with deep convolutional neural network for classifying images. International Journal of Scientific and Research Publications 09.