Segmentação de imagens e reconstrução de modelos aplicada a estruturas ósseas
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Data
2008-10-31
Autores
Marques, Adriano de Souza [UNESP]
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Editor
Universidade Estadual Paulista (Unesp)
Resumo
Na biomecânica, a computação tem se tornado uma forte aliada no estudo utilizando-se imagens, pois avanços significativos têm sido verificados devido à evolução das técnicas de aquisição de imagens médicas. Em estruturas ósseas, devido à complexidade das formas geométricas, a obtenção de modelos precisos torna-se um processo difícil, exigindo métodos computacionais igualmente complexos. Por outro lado, a computação gráfica oferece técnicas que possibilitam a adequada manipulação destas imagnes. Entre os diversos métodos existentes, o modelo de contornos ativos, também conhecido como snakes, vem sendo amplamente difundido no processo dd segmentação para extração de estruturas de interesse no contexto médico. Este trabalho utiliza o método de contornos ativos por Fluxo do Vetor Gradiente (GVF) para obtenção das matrizes do contorno de estruturas com geometrias côncavas, neste representado por seções transversais obtidas da tomografia de uma mandíbula humana. Utilizando-se as matrizes obtidas, é gerado um modelo da mandíbula em 3D aplicando-se o método de triangulação foi utilizado o pacote MATLAB®, e para obtenção do modelo tridimensional, foi utilizado o pacote ANSYS®.
In biomechanics, the computer has become a strong ally to study using the images, as significant advances have been recorded owing to technical progress of the acquisition of medical images. In bone structures due to the complexity of geometric shapes, to obtain accurate models becomes a difficult processes, requiring equally complex computational methods. On the other hand, offers computer graphics techniques that enable the appropriate handling of these images. Among the various existing methods, the model of active contours, also known as snakes, have been widely disseminated in hte process of segmentation to extract structures of interest medical. This work uses the method of active contours for Gradient Vector Flow (GVF) to obtain the matrices of the outline of structures with concave geometries, this represented by cross sections obtained from the tomography of a human jaw. Using the matrices obtained, it generated a 3D model of the jaw by applying the method of triangulation between adjacent contours. For the process of segmentation and triangulation was performed using MATLAB® application, and for obtaining three-dimensional model was performed using ANSYS® application.
In biomechanics, the computer has become a strong ally to study using the images, as significant advances have been recorded owing to technical progress of the acquisition of medical images. In bone structures due to the complexity of geometric shapes, to obtain accurate models becomes a difficult processes, requiring equally complex computational methods. On the other hand, offers computer graphics techniques that enable the appropriate handling of these images. Among the various existing methods, the model of active contours, also known as snakes, have been widely disseminated in hte process of segmentation to extract structures of interest medical. This work uses the method of active contours for Gradient Vector Flow (GVF) to obtain the matrices of the outline of structures with concave geometries, this represented by cross sections obtained from the tomography of a human jaw. Using the matrices obtained, it generated a 3D model of the jaw by applying the method of triangulation between adjacent contours. For the process of segmentation and triangulation was performed using MATLAB® application, and for obtaining three-dimensional model was performed using ANSYS® application.
Descrição
Palavras-chave
Processamento de imagens, Reconstrução 3D, Segmentação de imagens, Images - Computational methods
Como citar
MARQUES, Adriano de Souza. Segmentação de imagens e reconstrução de modelos aplicada a estruturas ósseas. 2008. 73 f. Dissertação (mestrado) - Universidade Estadual Paulista, Faculdade de Engenharia, 2008.