Reconstrução em 3D de imagens DICOM cranio-facial com determinação de volumetria de muco nos seios paranasais

• Ano de defesa: 2015
• Autor(a) principal: Lima, Rodrigo Freitas
• Orientador(a): Marengoni, Maurício
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Presbiteriana Mackenzie
• Palavras-chave em Português: imagens medicas; tomografia computadorizada; visualization toolkit; insight toolkit; MUNC (Maximum Unit Normal Component); DTA (Divergence Theorem Algorithm); renderização de volume; segmentação; visão computacional; seios paranasais
• Palavras-chave em Inglês: medical images; computer tomography; visualization toolkit; insight toolkit; MUNC (Maximum Unit Normal Component); DTA (Divergence Theorem Algorithm); volume rendering; segmentation; computer vision; sinuses
• Área do conhecimento CNPq: CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA
• Link de acesso: http://dspace.mackenzie.br/handle/10899/24379

Paranasal sinus are important objects of study to rhinosinusitis diagnostic, having some papers related incidence between asthma and allergic rhinitis.Many applications can calculate to various parts of the human body, getting a CT scan or MRI input, and returning information about the region of interest observed as volume and area. The accumulated mucus in the sinuses is one of the areas of interest that have not yet been implemented methods for the calculation of volume and area. In the present scenario, the patient monitoring is done visually, depending largely on perception of the evaluator. Therefore, we seek to implement more accurate metrics to facilitate medical care to the patient and it can help prevent the worsening of rhinitis in a given patient, developing mechanisms of visual and numerical comparison, where it is possible observe the progress of treatment. This work contains a detailed study of how certain existing techniques, combined into one methodology can segment and calculate the accumulated mucus in the maxillary sinus. In addition to techniques such as Thresholding, Gaussian filter, Mathematical Morphology, Metallic Artifacts Reduction during processing and segmentation, MUNC and DTA to calculate the volume and area, and visualization techniques as the Marching Cubes, it was also necessary some adjustments in the algorithm for limit the region of interest where the thresholding combined with the gaussian filter has not been effective of retaining edges. The application will use two open source platforms, one for processing, ITK, and another for visualization, VTK. The results demonstrated that it is possible to perform segmentation and the calculation with the use of platforms as well as the methodology used is adequate to solve this problem.