Computer Vision and Radiology for COVID-19 Detection

Autor: Ravneet Punia, Lucky Kumar, Mohd. Mujahid, Rajesh Rohilla
Rok vydání: 2020
Předmět:
Zdroj: 2020 International Conference for Emerging Technology (INCET)
DOI: 10.1109/incet49848.2020.9154088
Popis: 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.
Databáze: OpenAIRE