Deep Learning in Image Analysis for COVID-19 Diagnosis: a Survey
Keywords:Deep Learning, diagnosis, COVID-19, survey, Image analysis
COVID-19 achieved the highest concentration of confirmed cases in the Americas. A significant impact is expected in Latin America and the Caribbean region, where access to water and sanitation is restricted, and the health system suffers from a lack of human resources and equipment. In this scenario, we surveyed deep learning techniques applied to extract information from X-ray and computed tomography images to detect pneumonia caused by SARS-COV-2, directly assisting health professionals through an automatic case screening. We identify the main public and private image datasets of the disease, deep network architectures, and their performances. Thereby, we identified challenges and research directions. Thus, our goal is to provide a theoretical basis to contribute to the development of computational systems to aid the diagnosis of COVID-19.