Synetic superimposition of dental 3D data: application in twin studies

Three-dimensional measurement of dental morphology is providing new variables and shape information not available previously, and the reliability of these data has proved to be substantial. Accurate superimposition of 2D and 3D data-sets has several applications in dental research when making comparisons of similar structures. For example, two data-sets of the same object can be superimposed to highlight differences apparent in limited region(s) of the tooth crown. When significant regions represented by the two data-sets are identical, registration of the images can be achieved by standard superimposition methods. However, for comparisons of crown morphologies between monozygotic and dizygotic co-twins, the data sets are similar but not identical so a new approach to superimposition has been developed.

To develop a non 'best fit' (Synetic) method for the 3D superimposition of non-similar objects that forms one comparable interface providing enhanced methodology for the analysis of differences within the dentition of twins.

A minimised least-squares registration approach is followed by diffusion based registration to provide global minimisation between points that is not based on a best fit algorithm. This process is linear and therefore the method ensures uniqueness of the superimposition.

Initial results indicate a reliable method producing only one output as opposed to best fit approaches that may generate a different output each time.

Diffusion-based registration offers a more reliable approach to superimposing non-identical objects, such as the tooth crowns of monozygotic co-twins, than conventional best-fit methods.