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Master's Dissertation
DOI
10.11606/D.18.2009.tde-17112009-085347
Document
Author
Full name
Evandra Maria Raymundo
Institute/School/College
Knowledge Area
Date of Defense
Published
São Carlos, 2009
Supervisor
Committee
Rodrigues, Evandro Luis Linhari (President)
França, Celso Aparecido de
Paiva, Maria Stela Veludo de
Title in Portuguese
Metodologia de estimação de idade óssea baseada em características métricas utilizando mineradores de dados e classificador neural
Keywords in Portuguese
Classificadores neurais
Estimação de idade óssea
Imagem carpal
Mineração de dados
Segmentação de imagens
Abstract in Portuguese
Este trabalho apresenta uma proposta de metodologia de estimação de idade óssea baseada em características métricas, utilizando o banco de imagens carpais da Escola de Engenharia de São Carlos (EESC). As imagens foram devidamente segmentadas para obtenção da área, perímetro e comprimento de cada osso, gerando, assim, um banco de dados métricos o CarpEven. As informações da base métrica CarpEven foram submetidas a dois mineradores de dados: ao StARMiner, (Statistical Association Rules) uma metodologia de mineração de dados criada por um grupo de pesquisadores do ICMC-USP, e ao Weka (Waikato Environment for Knowledge Analysis), desenvolvido pela Universidade Waikato da Nova Zelândia. As informações foram submetidas a classificadores neurais, contribuindo, assim, para a criação de uma nova metodologia de estimação de idade óssea. Finalmente, é feita uma comparação entre os resultados obtidos e os resultados já alcançados por outras pesquisas.
Title in English
Methodology for bone age estimation based on metric characteristics using data mining and neural classifier
Keywords in English
Bone age estimation
Carpal image
Image segmentation
Mining
Neural classifiers
Abstract in English
This work presents a methodology for bone age estimation based on metric characteristics using the carpal images database from Engineering School of São Carlos (EESC-USP). The images were properly segmented to obtain the area, perimeter and length of each bone, thus generating a metric database named CarpEven. The database information were submitted to two data miners: the StarMiner (Statistical Association Rules Miner) a methodology for data mining created by a group of researchers from ICMC-USP, and the Weka (Waikato Environment for Knowledge Analysis), developed by the University of Waikato in New Zealand. The information was submitted to the neural classifiers contributing to the creation of a new methodology for bone age estimation. The results are compared with those obtained by others research.
 
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Evandra.PDF (1.77 Mbytes)
Publishing Date
2009-11-24
 
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