Fuzzy C means(FCM) clustering algorithm is one of well known unsupervised clustering techniques

which has been widely used in medical image segmentation. However

when the conventional FCM algorithm is used for image segmentation

no spatial information is taken into account. This causes the FCM algorithm to generate unexpected results of segmentation when dealing with noise of magnetic resonance images(MRI). Considering the intensities of ideal MRI are piecewise constant

we present an improved model to FCM algorithms using multiple objective programming. The algorithm can reasonably use the spatial information of the image and improve the accuracy of segmentation. The new algorithm is applied to both synthetic images and magnetic resonance images and the results show better robustness of our algorithm to noise and other artifacts than the conventional fuzzy image segmentation algorithms.