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Master's Dissertation
DOI
10.11606/D.45.2016.tde-20062016-125151
Document
Author
Full name
Daniel Oliveira Dantas
Institute/School/College
Knowledge Area
Date of Defense
Published
São Paulo, 2004
Supervisor
Committee
Barrera, Junior (President)
Cesar Junior, Roberto Marcondes
Reis, Luis Fernando Lima
Title in Portuguese
Uma técnica automática baseada em morfologia matemática para a medida de sinal de imagens de cDNA
Keywords in Portuguese
Microarray
Morfologia matemática
Segmentação
Abstract in Portuguese
O objetivo deste trabalho é apresentar uma técnica automática baseada em morfologia matemática para medida de sinal em imagens de cDNA desenvolvida no BIOINFO,em parceria com o Instituto Ludwig de Pesquisa contra o Câncer. A tecnologia de lâminas de cDNA é um processo baseado em hibridização que possibilita observar a concentração relativa de mRNA de amostras de tecidos analisando a luminosidade de sinais fluorescentes ou radioativos. Hibridização é o processo bioquímico onde duas fitas de ácido nucleico com seqüências complementares se combinam. A técnica apresentada permite o cálculo da expressão gênica com alto grau de automação, podendo o usuário corrigir com facilidade eventuais erros de segmentação. O usuário interage com o programa apenas para selecionar as imagens e inserir os dados de geometria da lâmina. A estratégia de solução usada tem três fases: gradeamento dos blocos, gradeamento dos spots e segmentação dos spots. Todas as fases utilizam filtros morfológicos e as fases de gradeamento possuem um passo final de correção baseado nos dados de geometria da lâmina o que aumenta a robustez do processo, que funciona bem mesmo em imagens ruidosas.
Title in English
An automated technique based on mathematical morphology for measuring signal from cDNA images
Keywords in English
Mathematical morphology
Microarray
Segmentation
Abstract in English
The objective of this work is to present the automated technique for measuring signal from cDNA images developed in BIOINFO, associated with the Ludwig Institute for Cancer Research. Microarray technology is a hybridization based process that makes possible to quantify the relative abundance of mRNA in two tissue samples analysing the luminosity of fluorescent or radioactive signals. Hybridization is a biochemical process where a strand of nucleic acid matches up its counterpart. The developed technique permits the calculation of gene expression with a high level of automation. Besides that, the user can easily correct eventual segmentation mistakes. The user interacts with the program only to select the images and to set the slide geometry parameters. The solution strategy has three main steps: subarray griding, spots gridding and spots detection. All the steps use morphological filters, and the two gridding steps have a final correction substep based on the slide geometry, increasing the process robustness, that works well even in noisy images.
 
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master_thesis.pdf (2.98 Mbytes)
Publishing Date
2016-06-22
 
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