### Figure 3

Schematic
illustrating different procedures in computational anatomy. After spatial normalization, one has access
to the normalized image and the deformation field implementing the
normalization. The deformation or tensor
field can be analyzed directly (deformation-based morphometry) or can be used
to derive maps of formal attributes (*e.g.*
compression, dilatation, shear *etc*.). These maps can then be subject to
conventional voxel-based analyses (tensor-based morphometry). Alternatively the normalized images can be
processed (*e.g.* segmented) to reveal
some interesting aspect of anatomy (*e.g.*
the tissue composition) and analyzed in a similar way (voxel-based
morphometry). Techniques developed for
tensor-based morphometry can be absorbed into voxel-based morphometry to prove
a unified framework. For example, before statistical analysis Jacobian, or
voxel-compression, maps can be multiplied by gray-matter density maps. This endows volumetric changes, derived from
the tensor, with tissue specificity, based on the segmentation.