resonance imaging (MRI) data and estimation

of intensity inhomogeneities using fuzzy logic. MRI intensity

inhomogeneities can be attributed to imperfections in the

radio-frequency coils or to problems associated with the acquisition

sequences. The result is a slowly varying shading artifact

over the image that can produce errors with conventional intensity-

based classification. Our algorithm is formulated by modifying

the objective function of the standard fuzzy c-means (FCM) algorithm

to compensate for such inhomogeneities and to allow the labeling

of a pixel (voxel) to be influenced by the labels in its immediate

neighborhood. The neighborhood effect acts as a regularizer

and biases the solution toward piecewise-homogeneous labelings.

Such a regularization is useful in segmenti