Computer vision and radiology for COVID-19 detection

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Abstract

COVID-19 is spreading rapidly throughout the world. As of 14 April 2020, 128, 000 people died of COVID-19, while 1.99 million cases in 210 countries and territories were reported in 219.747 cases. As the virus spreads at a very high rate, there is a huge shortage of medical testing kits all over the world. The respiratory system is the part of the human body most affected by the virus, so the use of X-rays of the chest may prove to be a more efficient way than the thermal screening of the human body. In this paper, we are trying to develop a method that uses radiology, i.e. X-rays for detecting the novel coronavirus. Along with the paper, we also release a dataset for the research community and further development extracted from various medical research hospital facilities treating COVID-19 patients.

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Punia, R., Kumar, L., Mujahid, M., & Rohilla, R. (2020). Computer vision and radiology for COVID-19 detection. In 2020 International Conference for Emerging Technology, INCET 2020. Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/INCET49848.2020.9154088

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