METODOLOGIA PARA DETECÇÃO AUTOMÁTICA DE NÓDULOS PULMONARES

• Ano de defesa: 2007
• Autor(a) principal: Sousa, João Rodrigo Ferreira da Silva
• Orientador(a): SILVA, Aristófanes Corrêa
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal do Maranhão
• Programa de Pós-Graduação: PROGRAMA DE PÓS-GRADUAÇÃO EM ENGENHARIA DE ELETRICIDADE/CCET
• Departamento: Engenharia
• País: BR
• Palavras-chave em Português: CAD; detecção automática de nódulos pulmonares; processamento de imagens; SVM; caracterização de nódulo
• Palavras-chave em Inglês: CAD; automatic lung nodule detection; image processing; SVM; nodule caracterization
• Área do conhecimento CNPq: CNPQ::ENGENHARIAS::ENGENHARIA BIOMEDICA
• Link de acesso: http://tedebc.ufma.br:8080/jspui/handle/tede/524

The lung cancer is a disorder with significant prevalence in several countries worldwide. The hard treatment and the fast progress of the disease increase the mortality rates. The main factor contributing to a successful treatment is an early diagnosis. However possible omissions in the scan analysis can lead to late diagnosis, compromising all the treatment. In order to present a computational tool aimed at nodules detection, that can be used as a second opinion to the specialist, this master thesis proposes a methodology for nodules detection that is totally automatic, robust and consistent. The methodology is based on successive refinements for the segmentation of computed tomography images using morphologic techniques to obtain nodule candidates. The false positive reduction is achieved by SVM based on geometric and texture features. The tests, performed with real scans, indicate the feasibility of the proposed method. In automatic detection performed on 33 cases the methodology reached 95.21% of correctness with 0.42 false positives and 0.15 false negative per scan.