Abstract: A novel active contour models based on fuzzy C-means energy minimization is put forward.First,the proposed method uses fuzzy C-means clustering to segment images to obtain the fuzzy membership degree value of image foreground and background.Subsequently,the local pixel information of the target area and its membership degree value is used as the initial value of the level set function of the active contour model.The proposed method applies a fast algorithm to directly calculate the energy minimization of the fuzzy C-means membership degree value and drive the curve evolution of the traditional active contour model.The method avoids solving Euler-Lagrange equation.The proposed method is compared with the classic active contour model segmentation algorithms.The experiment is performed on simulated and the clinical ultrasonic images.It shows that the proposed algorithm can effectively segment ultrasound images with good segmentation performance and reasonable speed.The method can solve the problems of intensity inhomogeous,fuzzy boundaries and speckle noise.