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Master's Dissertation
DOI
10.11606/D.18.2001.tde-11122001-004011
Document
Author
Full name
Andres Anobile Perez
Institute/School/College
Knowledge Area
Date of Defense
Published
São Carlos, 2001
Supervisor
Committee
Gonzaga, Adilson (President)
Alves, Jose Marcos
Imamura, Marta
Title in Portuguese
Segmentação e quantificação de tecidos em imagens coloridas de úlceras de perna.
Keywords in Portuguese
diagnóstico assistido por computador
processamento de imagens coloridas
segmentação
úlceras de perna
visão computacional
Abstract in Portuguese
Neste trabalho foi desenvolvida uma metodologia de avaliação e monitoramento de pacientes com úlceras de perna baseada nas características dos tecidos internos dessas feridas. Os tecidos internos podem ser classificados como granulado, fibrina e necrosado, e a avaliação da área de cada um desses tecidos fornece para o clínico dados referentes ao estado da úlcera.A metodologia extrai essas informações a partir de imagens digitalizadas das lesões. Para tanto, a área referente à úlcera é segmentada e em seguida a área interna processada por uma rede neural, que tem o propósito de classificar cada ponto para um dos tecidos analisados. Os algoritmos desenvolvidos operam sobre imagens coloridas, já que cada tecido em uma imagem só pode ser identificado por sua cor. Este trabalho propõe ainda uma metodologia de extração de características das lesões através de uma forma não invasiva utilizando, para tanto, algoritmos de visão computacional.
Title in English
Segmentation and quantification of tissues in leg ulcers color images
Keywords in English
color image processing
computer vision
computer-aided diagnosis
leg ulcers
segmentation
Abstract in English
The aim of this work was the development of a monitoring and evaluation methodology of leg ulcers patients based on the features of the inner tissues of these wounds. The internal tissues can be classified as granulation, slough and necrotic, and the evaluation of the area of each one of these tissues can be used by the specialist to help with the patient''s diagnosis. The methodology extracts these information from the wound digitized images. For this, the wound area is segmented and the inner region or the segmented area is processed by a neural network that classifies each point of the analyzed tissues. The developed algorithms operate on color images since each tissue in an image can only be analyzed by its colors. In this work has also proposed a feature extraction methodology of the wounds through a non-invasive way using computer vision algorithms.
 
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Apendice1.pdf (278.57 Kbytes)
Apendice2.pdf (26.00 Kbytes)
bibliografia.pdf (9.79 Kbytes)
Cap1.pdf (12.63 Kbytes)
Cap2.pdf (48.07 Kbytes)
cap3.pdf (251.90 Kbytes)
Cap4.pdf (193.41 Kbytes)
Cap5.pdf (101.47 Kbytes)
cap6.pdf (686.05 Kbytes)
Cap7.pdf (259.00 Kbytes)
Cap8.pdf (30.74 Kbytes)
capa_e_resumo.pdf (43.50 Kbytes)
Publishing Date
2001-12-17
 
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