This paper introduces a new formula for the objective
function of the famous fuzzy C-means algorithm. Two
weighted terms are added to the objective function to reflect
any available information about the class center and class
pixels distribution throughout the datasets. The algorithm is
evaluated for the task of the segmentation of medical MRI
brain volume. The results show that the algorithm has a
considerable robustness against noise and partial volume
effects, and it needs a smaller number of iterations to reach
convergence compared with other similar algorithms.