ITM Web Conf.
Volume 44, 2022International Conference on Automation, Computing and Communication 2022 (ICACC-2022)
|Number of page(s)||6|
|Published online||05 May 2022|
Automated Lung Semantic Segmentation on X-Ray Using Convolutional Models
Ramrao Adik Institute Of Technology, Electronics And Telecommunication Engineering, Navi Mumbai, Maharashtra, India
* Corresponding author: email@example.com
Towards the culmination of 2019, an outburst of coronavirus disease 2019 (COVID-19) pandemic struck mankind, which was instigated due to severe acute respiratory syndrome (SARS) which originally transpired from Wuhan City, China. Myriad of people have acceded to this disease. The effects of the pandemic have been more severe on the populous nations of the world. In India, although over 1.5 billion vaccinations have been provided to the inhabitants, as of 21 February 2022, the pandemic has barely diminished, as seen in Figure 1.1. While restrictions are being somewhat relaxed, the chances of the ominous ’4th wave’ materialises large. In such scenarios, it is of supreme importance to have apparatus for rapid testing and diagnosis of the disease, to expedite a much faster process. This paper will give an insight of a model that can efficiently and precisely predict the presence of COVID-19 by using a CT scan of the lungs.
© The Authors, published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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