Abstract:
Several recent research papers have shown the usefulness of Deep Learning (DL) techniques for COVID-19 screening in Chest X-Rays (CXRs). To make this technology accessible and easy to use, a natural path is to leverage the widespread use of smartphones. In these cases, the DL models will inevitably be presented with photographs taken with such devices from a computer monitor. Thus, in this work, a dataset of CXR digital photographs taken from computer monitors with smartphones is built and DL models are evaluated on it. The results show that the current models are not able to correctly classify this kind of input. As an alternative, we build a model that discards pictures of monitors such that the COVID-19 screening module does not have to cope with them.
