Segmentation of Brain Tumor on MRI Images Using Modified GVF Snake Model

Medical image segmentation is the most important process and research focus in the medical image processing field. Snakes, or active contours, are used extensively in computer vision and image processing applications, particularly to locate object boundaries. In this paper the gradient vector flow (GVF) snake model is modified with thinning canny edge detection is used for brain tumor segmentation. The thinning canny operator is used to calculate the edge map gradient for GVF snake model. Then the GVF deforms with initial contour. Simulation results show that the GVF model with thinning canny operator can extract the boundary of brain tumor accurately. This method can overcome the problem that traditional snake cannot have efficient converge to the weak boundary.