Dealing with difficult deformations: Construction of a knowledge-based deformation atlas

Signe Strann Thorup, Tron A. Darvann, Nuno W. Hermann, Per Larsen, Hildur Olafsdottir, Rasmus R. Paulsen, A. A. Kane, D. Govier, L. J. Lo, Sven Kreiborg, Rasmus Larsen

AbstractTwenty-three Taiwanese infants with unilateral cleft lip and palate (UCLP) were CT-scanned before lip repair at the age of 3 months, and again after lip repair at the age of 12 months. In order to evaluate the surgical result, detailed point correspondence between pre- and post-surgical images was needed. We have previously demonstrated that non-rigid registration using B-splines is able to provide automated determination of point correspondences in populations of infants without cleft lip. However, this type of registration fails when applied to the task of determining the complex deformation from before to after lip closure in infants with UCLP. The purpose of the present work was to show that use of prior information about typical deformations due to lip closure, through the construction of a knowledge-based atlas of deformations, could overcome the problem. Initially, mean volumes (atlases) for the pre- and post-surgical populations, respectively, were automatically constructed by non-rigid registration. An expert placed corresponding landmarks in the cleft area in the two atlases; this provided prior information used to build a knowledge-based deformation atlas. We model the change from pre- to post-surgery using thin-plate spline warping. The registration results are convincing and represent a first move towards an automatic registration method for dealing with difficult deformations due to this type of surgery. New or breakthrough work to be presented: The method provides a simple way of dealing with complex morphological changes using knowledge of typical deformations.
TypeConference paper [With referee]
ConferenceProceedinsg of SPIE, Medical Imaging 2010: Biomedical Applications in Molecular, Structural, and Functional Imaging
Year2010
ISBN / ISSNDOI: 10.1117/12.845670
BibTeX data [bibtex]
IMM Group(s)Image Analysis & Computer Graphics