Segmentation of the brain from 3-D magnetic resonance images of the head

An automated procedure for segmentation of the brain from 3-D MR images of the head is described. This process combines some heuristics with a number of three-dimensional image processing and computer vision techniques including seed-based volume growing, DOG convolution and zero-crossing detection, convolution with the Zucker-Hummel operator, and watershed anaylsis. There are two broad steps: (1) rough estimation of brain voxels, and (2) refinement of the first step through a reverse-gravity watershed analysis. All operations are performed in three-dimensions in order to fully utilize the information present in the voxels generated by the 3-D MP-RAGE sequence.