DISSERTAÇÃO DE MESTRADO - PROGRAMA DE PÓS-GRADUAÇÃO EM CIÊNCIA DA COMPUTAÇÃO
URI Permanente para esta coleçãohttps://tedebc-teste.ufma.br/handle/tede/1314
Áreas de Concentração e Linhas de Pesquisa:
Automação e Contrôle
Ciência da Computação
Sistemas de Energia Elétrica
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Navegando DISSERTAÇÃO DE MESTRADO - PROGRAMA DE PÓS-GRADUAÇÃO EM CIÊNCIA DA COMPUTAÇÃO por Assunto "Adversarial training"
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Item Segmentação automática da próstata em imagens de ressonância magnética utilizando redes neurais convolucionais, mapa probabilístico e treinamento adversário(Universidade Federal do Maranhão, 2019-02-15) FERREIRA, Jonnison Lima; PAIVA, Anselmo Cardoso de; 375523843-87; http://lattes.cnpq.br/6446831084215512; SILVA, Aristófanes Corrêa; 288745363-72; http://lattes.cnpq.br/2446301582459104; SILVA, Aristófanes Corrêa; 288745363-72; http://lattes.cnpq.br/2446301582459104; PAIVA, Anselmo Cardoso de; 375523843-87; http://lattes.cnpq.br/6446831084215512; CAVALCANTE, André Borges; http://lattes.cnpq.br/3885279033465023; BRAZ JÚNIOR, Geraldo; http://lattes.cnpq.br/8287861610873629; CARVALHO FILHO, Antonio Oseas de; http://lattes.cnpq.br/7913655222849728Prostate cancer is the second most common cancer among men, being the second most deadly. Early detection is a strategy to find the tumor at an early stage and thus provide a better chance of treatment. Currently the prostate gland imaging test has grown for prevention, diagnosis and treatment. The manual segmentation of the prostate is delayed and the propensity to variability among those expected, due to work, alternatives such as computational systems that use image processing and the identification of more advanced and exploited patterns for the early diagnosis of this disease, providing a second opinion for the specialist and increase the process. In this work, several automatic tasks are provided for the segmentation of the prostate from magnetic resonance imaging using a deep learning technique, probabilistic mapping and adversarial training of neural networks. The proposed methodology was tested on two public imaging databases, the Prostate 3T prostate and the PROMISE12, resulting in an average Dice of 89%.