This paper addresses the segmentation problem in noisy image based on Fast Edge Integration (FEI) method in active contour model (ACM) and proposes a new statistical active contour model (SACM). Two modifications are performed in FEI method. First, in order to handle noisy images, maximum log-likelihood estimation is used to replace the minimal variance term proposed by Chan and Vese. Second, a penalising term is employed to replace the time consuming re-initialization process. The proposed SACM is evaluated and compared with the existing ACM-based algorithms in terms of segmentation results and computational time. The proposed SACM outperforms existing methods and requires much less computational time.