Filtragem de sinograma tomográfico afetado por ruído Poisson utilizando wavelets anisotrópicas

• Ano de defesa: 2017
• Autor(a) principal: Pinheiro, Arthur Melo
• Orientador(a): Mascarenhas, Nelson Delfino d'Ávila
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de São Carlos; Câmpus São Carlos
• Programa de Pós-Graduação: Programa de Pós-Graduação em Ciência da Computação - PPGCC
• Palavras-chave em Português: Processamento de imagens; Tomografia computadorizada; Fltragem de ruído; Ruído Poisson
• Área do conhecimento CNPq: CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
• Link de acesso: https://repositorio.ufscar.br/handle/20.500.14289/8800

The diagnostic imaging by computed tomography has become popular in recent decades. As the image acquisition method is effected by exposing the human body to X-ray dose (ionizing radiation), the frequent realization of diagnoses results in the accumulation of radiation, and may be a significant factor in the emergence of cancer diseases. This problem has motivated researchers to develop methods to reduce the dose of X-rays so that the image quality can be maintained. A common methodology involves applying algorithms for filtering noisy tomographic images that can be acquired under low dose of X-rays. This process may occur in the reconstructed image domain or tomographic projections domain. This work proposes a methodology for applying filtering Poisson noise present in tomographic sinogram, which uses the main anisotropic wavelets studied by the scientific community, which are: Curvelet, Contourlet, Shearlet. These wavelets apply the concept of multiscale and multidirectional analysis in a multidimensional signal, and may be advantageous in two-dimensional analysis of sinogram, preserving better image details in a noise reduction process compared to orthogonal wavelets.