COVID-19 detection from Xray and CT scans using transfer learning

Berrimi, Mohamed; Hamdi, Skander; Yahia Cherif, Raoudha; Moussaoui, Abdelouahab; Oussalah, Mourad; Chabane, Mafaza (2021-05-25)
 
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https://doi.org/10.1109/WiDSTaif52235.2021.9430229

Berrimi, Mohamed
Hamdi, Skander
Yahia Cherif, Raoudha
Moussaoui, Abdelouahab
Oussalah, Mourad
Chabane, Mafaza
Institute of Electrical and Electronics Engineers
25.05.2021

M. Berrimi, S. Hamdi, R. Y. Cherif, A. Moussaoui, M. Oussalah and M. Chabane, "COVID-19 detection from Xray and CT scans using transfer learning," 2021 International Conference of Women in Data Science at Taif University (WiDSTaif ), 2021, pp. 1-6, doi: 10.1109/WiDSTaif52235.2021.9430229

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doi:https://doi.org/10.1109/WIDSTAIF52235.2021.9430229
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https://urn.fi/URN:NBN:fi-fe2021100449271
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Abstract

Since the novel coronavirus SARS-CoV-2 outbreak, intensive research has been conducted to find suitable tools for diagnosis and identifying infected people in order to take appropriate action. Chest imaging plays a significant role in this phase where CT and Xrays scans have proven to be effective in detecting COVID-19 within the lungs. In this research, we propose deep learning models using Transfer learning to detect COVID-19. Both X-ray and CT scans were considered to evaluate the proposed methods.

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