Robust active contour segmentation with an efficient global optimizer

Active contours or snakes are widely used for segmentation and tracking. Recently a new active contour model was proposed, combining edge and region information. The method has a convex energy function, thus becoming invariant to the initialization of the active contour. This method is promising, but has no regularization term. Therefore segmentation results of this method are highly dependent of the quality of the images. We propose a new active contour model which also uses region and edge information, but which has an extra regularization term. This work provides an efficient optimization scheme based on Split Bregman for the proposed active contour method. It is experimentally shown that the proposed method has significant better results in the presence of noise and clutter

A Novel Segmentation Approach Combining Region- and Edge-Based Information for Ultrasound Images

Ultrasound imaging has become one of the most popular medical imaging modalities with numerous diagnostic applications. However, ultrasound (US) image segmentation, which is the essential process for further analysis, is a challenging task due to the poor image quality

Filtro de difusão anisotrópico orientado por evidência de borda

Dissertação (mestrado) - Uiversidade Federal de Santa Catarina, Centro Tecnológico. Programa de Pós-Graduação em Ciência da ComputaçãoFiltro de Difusão Anisotrópico é uma técnica bem estabelecida para melhoria de imagens que pode ser empregada para suavização de imagens ainda preservando alguma informação de borda. Entretanto, quando é necessário aplicar muitas iterações do filtro, gradualmente as bordas desaparecerão e serão esmaecidas pelo processo. Este trabalho propôs a adoção de mapa de gradientes coloridos para guiar o processo de suavização que claramente define quais bordas serão preservadas depois de muitas iterações. Como característica adicional, o método proposto emprega informações estatísticas para variar o parâmetro de lambda dinamicamente durante a filtragem, permitindo uma suavização adaptativa mais sensível. Os resultados alcançados demonstram-se superiores quando comparados com o filtro tradicional. Anisotropic diffusion filter is a well-established technique for image enhancement that can be employed to smooth images while preserving some degree of edge information. However, when it becomes necessary to apply a large number of filtering iterations, edges gradually fade away and are ultimately smoothed by the process. We propose the adoption of a color gradient map to guide the smoothing so that clearly-defined edges are preserved even after many iterations. As an additional feature, our method employs the statistical information to vary the lambda parameter dynamically during filtering, allowing for a more sensitive adaptive smoothing. The results achievied show good results when compared with traditional filter