We conduct a comparative evaluation of chest X-ray and computed tomography (CT) scan imaging modalities for machine learning-based automatic COVID-19 diagnosis. Using a public corpus of 17,599 medical images, we applied transfer learning with MobileNetV2 to assess diagnostic accuracy, sensitivity, and specificity and established that CT scans are more accurate than X-rays, yet X-rays are more sensitive to non-COVID cases, and therefore have complementary roles in clinical practice.
Keywords— COVID-19 screening, Medical imaging, Chest X-ray, Computed tomography (CT) scan, Machine learning, Deep learning, Transfer learning, Image reprocessing, Artifact removal, Deblurring, AI-aided diagnosis, Data augmentation,Diagnostic accuracy, Multimodal imaging.

Auteurs : Jawhara Lazhar , Boutheina Ben-Ismail, Wyssem Fathallah, Hedi Sakli

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