In this paper, we propose fully 3D active surface models for image segmentation. Our models are capable of fitting a diverse range of region shapes. They have low sensitivity to initial shape and position. We design self--inflation/deflation forces, which cooperate naturally with gradient forces. They permit the active surface to travel a long distance without the aid of any external forces. They are easily controlled in both their directions and magnitude. The models produce accurate segmentation when tested with synthetic and real images. They manifest robustness to image noise and imperfect image data. Importantly, they are capable of converging to the correct boundary even if the initial estimate is not close.