Segmentation of ultrasound images of liver tumors applying snake algorithms and GVF

Given the high concentration of blood vessels in liver, and the speckle noise inherent in ultrasound imagery, segmenting liver tumors in ultrasound images is a hard problem. Snakes, or active contours, have had limited success in such noisy and complex images. By coupling the smoothness of the edge map to the initial size of the snake, enhancing the tumor boundaries, tuning the regulating parameters of the snake, and an improved numerical approximation of a vector diffusion equation of the gradient vector field, we have obtained good results on 12 ultrasound images of liver tumors of various sizes.