A shortcoming of this approach, however, was that more current (and computationally intense) high-dimensional warping approaches such as the commonly-employed DARTEL-  or SHOOT-approach  use an iterative self-registration scheme. Hence, a single tissue prior is not appropriate anymore as these approaches require an increasingly crisp set of tissue priors to register to. The DARTEL-approach has shown great accuracy when compared with other non-linear spatial deformation approaches  and was later refined .1 To generate such high-quality tissue maps, however, large populations are required  which may not always be available, especially in the case of an “unusual” population such as children or elderly subjects. The here-described parameter set is the result of using the CerebroMatic toolbox to statistically generate such tissue prior sets for ultimate use within the DARTEL/SHOOT framework, based on a large population of healthy infants, children, and young as well as older adults.