A novel active contour model for image segmentation using distance regularization term

In this paper, a novel active contour model (R-DRLSE model) based on level set method is proposed for image segmentation. The R-DRLSE model is a variational level set approach that utilizes the region information to find image contours by minimizing the presented energy functional. To avoid the time-consuming re-initialization step, the distance regularization term is used to penalize the deviation of the level set function from a signed distance function. The numerical implementation scheme of the model can significantly reduce the iteration number and computation time. The results of experiments performed on some synthetic and real images show that the R-DRLSE model is effective and efficient. In particular, our method has been applied to MR kidney image segmentation with desirable results.