Soares, Heliana BezerraCaro, João Pedro Betanza Dal2022-12-232022-12-232022-12-21CARO, João Pedro Betanza Dal. Segmentação da pneumonia causada por COVID-19 em imagens tomográficas. Orientador: Heliana Bezerra Soares. 2022. 57 f. Trabalho de Conclusão de Curso (Graduação em Engenharia Biomédica) - Centro de Tecnologia, Universidade Federal do Rio Grande do Norte, 2022.https://repositorio.ufrn.br/handle/123456789/50591With the arrival of the COVID-19 pandemic, caused by the new coronavirus Sars-CoV-2, there was a global race in search of methods to diagnose the disease and understand its effects on the human body. As most severe cases refer to pulmonary infections, the effects of the virus in the lungs reached high interest for the area research, popularizing the usage of computed tomography (CT) chest scans. Aiming to ease the healthcare professional’s follow-up, this work presents an algorithmic strategy with the objective of segmenting the COVID-19 compromised region within the lungs. Using morphologic operations and an adaptive limiarization technique to achieve lung and infection masks, the algorithm could suggest a compromise rate with a mean error of 3.55%. It also presented a mean accuracy of 99.11% and a specificity of 99.65%.Attribution-NonCommercial-NoDerivs 3.0 Brazilhttp://creativecommons.org/licenses/by-nc-nd/3.0/br/COVID-19SegmentaçãoProcessamento digital de imagensTomografiaComprometimento pulmonarSegmentationDigital imaging processingTomographyLung compromisebachelorThesis