DETECTION OF COVID-19 IN COMPUTED TOMOGRAPHY IMAGES USING DEEP LEARNING: A LITERATURE REVIEW

Resumo

Several diagnostic imaging methods are being studied with the development of the COVID-19 disease. One of them is computed tomography (CT), which has the best level of de- tail among medical imaging exams. CT generates a repet- itive and tiring workload, in addition to requiring a team familiar with the findings that indicate pneumonia caused by COVID-19. Several studies were carried out using deep learning techniques to reduce manual work and collaborate with teams and experts. Thus, this study presents a re- view of the literature regarding the detection of COVID-19 in CT that uses deep learning. We present here the main techniques used, such as pre-processing, segmentation, and the main models for classification. We also present several image bases that are publicly available. All this contributes to a theoretical basis for future work.

DOI: 10.36558/rsc.v12i1.7588