Image segmentation technology is an important part of the lower level of computer vision. It′s also a basic precondition for image analysis and pattern recognition. It has been widely used in many fields such as medical images and remote sensing images. Meanwhile, image segmentation is a difficulty in image processing as well. Aiming at medical imagery, a novel variational domain approach to curve evolution for image segmentation is proposed based on a statistical active contour model using level sets. The essential idea is to re-define the computing domain in image repeatedly by separating the segmentation procedure into several individual phases. By our algorithm, the work can be done automatically without manual intervention. Moreover, compared with current methods, the rapidity can be enhanced effectively for the objects with complicated topology.