The 3D-CSC is a general segmentation method for voxel images. One of its possible applications is the segmentation
of MR images of the human head. We here propose a self-contained method consisting of preprocessing
steps which remove common artifacts from the input image, a 3D-CSC segmentation which partitions the input
image into gray value similar, spatially connected regions and a final classification of CSC segments into white
matter, gray matter and non-brain. We evaluate our method using the brainweb dataset for which a ground
truth is available.