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Master's Dissertation
DOI
10.11606/D.55.2016.tde-17112016-101608
Document
Author
Full name
Paulo Duarte Barbieri
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Carlos, 2016
Supervisor
Committee
Traina, Agma Juci Machado (President)
Barbosa, Marcello Henrique Nogueira
Schiabel, Homero
Title in Portuguese
Explorando superpixels para a segmentação semiautomática de imagens médicas para recuperação por conteúdo
Keywords in Portuguese
Corpos vertebrais
Imagens médicas
Segmentação
Superpixels
Abstract in Portuguese
Nesse trabalho foi desenvolvido o método VBSeg, um método de segmentação semiautomático de corpos vertebrais, que utiliza superpixels para aumentar a eficiência de técnicas de segmentação de imagens já estabelecidas na literatura, sem perder qualidade do resultado final. Experimentos mostraram que o uso de superpixels melhorou o resultado da segmentação dos corpos vertebrais em até 18%, além de aumentar a eficiência desses métodos, deixando a execução dos algoritmos de segmentação pelo menos 38% mais rápida. Além disso, o método desenvolvido possui baixa dependência do nível de especialidade do usuário e apresentou resultados comparáveis ao método Watershed, um método bem estabelecido na área de segmentação de imagens. Contudo, o método VBSeg segmentou 100% dos corpos vertebrais das imagens analisadas, enquanto que o método Watershed deixou de segmentar 44% dos corpos.
Title in English
Exploring superpixels to semi automatic medical image segmentation for content-based image retrieval
Keywords in English
Medical images
Segmentation
Superpixels
Vertebral bodys
Abstract in English
This work presents the development of a semiautomatic vertebral body segmentation method VBSeg, which uses superpixels to increase effi- ciency of well established image segmentation methods without losing quality. Experiments have shown motivating results with superpixels im- proving vertebral bodies segmentation in 18% and making segmentation algorithms at least 38% faster. Furthermore, our VBSeg method has low dependency on the level of expertise and got similar results to Watershed method, a well-established image segmentation method. However, VB- Seg method was able to segment 100% of the analyzed vertebral bodies while Watershed method missed 44% of those.
 
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Publishing Date
2016-11-17
 
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