Automatic medical image segmentation based on EPGV-Snake
Houda Bakir, Maher Charfi · 2009
This communication presents a novel approach to contour segmentation of computed tomography (CT) images. Image segmentation is achieved by means of the snake algorithm and the dynamic programming (DP) optimization technique. Based upon the edge preserving gradient vector flow (EPGVF) field, a new strategy for contour points initialization and splitting is presented. Contour initialization is carried out from EPGVF magnitude thresholding. In the multi-object image segmentation, the delineation of all the image objects is done through the splitting of the contour at the divergent points in the image. The proposed technique can attain a good solution without the need of an operator intervention. Some experiences on synthetic and CT medical images show that the proposed algorithm gives good results.