Automatic distinction between COVID-19 and common pneumonia using multi-scale convolutional neural network on chest CT scans

Abstract

Highlights A CT dataset contains 416 COVID-19 positive CT scans and 412 common pneumonia CT scans is publicly available. A multi-scale convolutional neural network can accurately differentiate COVID-19 and other common pneumonia on chest CT scans with limited number of training data. An AI system has comparable diagnostic sensitivity (89.1% vs 84.8%, p -value = 0.724), specificity (85.7% vs 83.3%, p -value = 1.000), and accuracy (87.5% vs 84.1%, p -value = 0.804) than experienced radiologists.

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