Introduction Segmentation and classification are the major and most difficult steps in image analysis. This yields information concerning the tissue distribution in human body. Knowledge of tissue distribution allows the creation of anatomical models of human body. Segmentation Segmentation is the division of an image or a volume scan in objects, which are represented by homogeneous regions. Characteristics can be combined and used to derive structural, spectral or statistical features.
Region growing means that voxels are collected starting from a set of seed points.
Region growing is an iterative process, finishing if no neighboring voxels fit in the region characteristics. The octtree is a hierarchical data structure that specifies the occupancy of cubic regions of object space. A cubic region, representing the whole object space, forms the node at the root of a tree. The segment representation of a volume dataset supports tissue classification. Wellknown representatives of numerical methods are geometrical and statistical classificators.