Crouzon syndrome is characterized by premature fusion of sutures and synchondroses. Recently, the first mouse model of the syndrome was generated, having the mutation Cys342Tyr in Fgfr2c, equivalent to the most common human Crouzon/Pfeiffer syndrome mutation. In this study, a set of micro-computed tomography (CT) scannings of the skulls of wild-type mice and Crouzon mice were analysed with respect to the dysmorphology caused by Crouzon syndrome. A computational craniofacial atlas was built automatically from the set of wild-type mouse micro-CT volumes using (1) affine and (2) non-rigid image registration. Subsequently, the atlas was deformed to match each subject from the two groups of mice. The accuracy of these registrations was measured by a comparison of manually placed landmarks from two different observers and automatically assessed landmarks. Both of the automatic approaches were within the interobserver accuracy for normal specimens, and the non-rigid approach was within the interobserver accuracy for the Crouzon specimens. Four linear measurements, skull length, height and width and interorbital distance, were carried out automatically using the two different approaches. Both automatic approaches assessed the skull length, width and height accurately for both groups of mice. The non-rigid approach measured the interorbital distance accurately for both groups while the affine approach failed to assess this parameter for both groups. Using the full capability of the non-rigid approach, local displacements obtained when registering the non-rigid wild-type atlas to a non-rigid Crouzon mouse atlas were determined on the surface of the wild-type atlas. This revealed a 0.6-mm bending in the nasal region and a 0.8-mm shortening of the zygoma, which are similar to characteristics previously reported in humans. The most striking finding of this analysis was an angulation of approximately 0.6 mm of the cranial base, which has not been reported in humans. Comparing the two different methodologies, it is concluded that the non-rigid approach is the best way to assess linear skull parameters automatically. Furthermore, the non-rigid approach is essential when it comes to analysing local, non-linear shape differences.