Gradient Vector Flowdriven Active Shape for Image Segmentation

We describe a gradient vector flow driven active shape method for model-based image segmentation. Active shape algorithm retain the shape feature of the interested object, and its performance relies heavily on initialization. Because of a lack of global regulation, the control points tends to be trapped in a local optimum in searching. Our proposed method uses the gradient vector flow of an image to guide the optimization process. The control points of an active shape are steered by the direction and the magnitude of gradient vectors. Our experiments demonstrated great improvement in finding the global optimum and resulting correct segmentation.