VBM5 (for SPM5)

The segmentation algorithm in SPM5 additionally warps the prior images to the data and tries to minimize the impact of the template and the prior images (Ashburner & Friston, 2005). Therefore we can use the segmentation without the modifications made for SPM2 known as optimized VBM procedure. Thus, for most cases there is no need to create a customized template or even customized priors. The VBM5 toolbox extends the core segmentation algorithm by the HMRF approach and some other useful options. A very helpful option is that you can use previously estimated segmentations to save segmentations using different voxel size, to save additional tissue classes, or to apply MRF and clean-up steps.

Schematic overview about the unified segmentation approach in SPM5. The first 40 iterations of the initial segmentation estimation are followed by 40 iterations of bias filed correction and finally 20 iterations are made for warping the prior image to the data. This iterated scheme is repeated until no significant changes occur.