COVID-19 detection from Xray and CT scans using transfer learning
Mohamed Berrimi, Skander Hamdi, Raoudha Yahia Cherif, Abdelouahab Moussaouı, Mourad Oussalah, Mafaza Chabane
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.
Topics & Concepts
Coronavirus disease 2019 (COVID-19)Transfer of learningSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Computer science2019-20 coronavirus outbreakDeep learningArtificial intelligenceComputed tomographyOutbreakMachine learningMedical physicsRadiologyMedicineVirologyPathologyInfectious disease (medical specialty)DiseaseCOVID-19 diagnosis using AIRadiomics and Machine Learning in Medical ImagingAI in cancer detection