SARS-CoV-2 Induced Pneumonia Early Detection System Based on Chest X-Ray Images Analysis by Jacobian-Regularized Deep Network.

SARS-CoV-2 induced disease (Covid-19) was declared as a pandemic by the World Health Organization in March 2020. It was confirmed as severe disease which induces pneumonia followed by respiratory failure. Real-Time Polimerase Chain Reaction (RT-PCR) is the de-facto standard diagnosis for Covid-19 but due to the cost and processing-time it is inapplicable for large screening programs. By contrast, Chest X-Ray (CXR) imaging analysis offers a fast, sustainable and performing approach for the early detection of Covid-19 disease. The proposed solution consists of a novel end-to-end intelligent system for CXR analysis embedding lung segmentation and an innovative 2D-to-3D augmentation approach in order to provide a robust classification of input CXR as viral (no Covid-19 pneumonia), Covid-19 pneumonia and healthy subject. Furthermore, in order to make a robust classification process we have implemented a compensation mechanism for adversarial attacks phenomena on CXR images using Jacobian regularization techniques. The collected performance results confirmed the effectiveness of the designed pipeline.