Brain tissue segmentation using improved kernelized rough-fuzzy C-means with spatio-contextual information from MRI.

Segmentation of brain tissues from MRI often becomes crucial to properly investigate any region of the brain in order to detect abnormalities. However, the accurate segmentation of the brain tissues is a challenging task as the different tissue regions are usually imprecise, indiscernible, ambiguous, and overlapping. Additionally, different tissue regions are non-linearly separable.