RESUMO
Snakes, or active contour models, have been widely used in image segmentation. However, most present snake models do not discern between positive and negative step edges. In this paper, a new type of dynamic external force for snakes named dynamic directional gradient vector flow (DDGVF) is proposed that uses this information for better performance. It makes use of the gradients in both x and y directions and deals with the external force field for the two directions separately. In snake deformation, the DDGVF field is utilized dynamically according to the orientation of snake in each iteration. Experimental results demonstrate that the DDGVF snake provides a much better segmentation than GVF snake in situations when edges of different directions are present which pose confusion for segmentation.
Assuntos
Algoritmos , Inteligência Artificial , Aumento da Imagem/métodos , Interpretação de Imagem Assistida por Computador/métodos , Imageamento Tridimensional/métodos , Armazenamento e Recuperação da Informação/métodos , Reconhecimento Automatizado de Padrão/métodos , Reprodutibilidade dos Testes , Sensibilidade e EspecificidadeRESUMO
In this paper, an automated method of boundary detection of the left ventricle (LV) is proposed. The method uses a watershed transform and morphological operation to locate the region containing the LV, then performs snake deformation with a multiscale directional edge map for the detection of the endocardial boundary of the LV.
