A ridge curve on the human skull is an extended "sharp edge," such as the lower border of the jaw or the rim of the orbit. Ridge curves have been applied to problems of face recognition, multimodal registration, and medical image segmentation. They concentrate information about form in an unusually concise and useful way. But the quantitative use of these curves is so new, that analytic and statistical techniques for dealing with the information they contain are almost unavailable. In studies, of which this proposal is a continuation, the applicant and his colleagues have shown how to pass from a cranial CT scan to a normative atlas of points, ridge curves, and surface patches bounded by curves that summarize the specimen form as the deformation of an averaged skull. While the landmarks of this representation continue to incorporate useful information about differences of form, the curves and patches have been shown, unequivocally, to contain information about those differences beyond what is measurable using landmarks. In this competing renewal, techniques will be developed for analyzing these curves. Aim 1 is to install a new, more robust algorithm for their location. In Aim 2, a preliminary statistical description will be extended into a more complete system for reporting findings in the clinically familiar language of bulges and deficits of bone. Aims 3 and 4 will apply those extended methods to two new data sets for which conventional approaches have not been helpful, including differential diagnosis of the cranial vault in the synostosis syndromes, and description of the postsurgical nose in unilateral cleft lip and palate. If successful in these four aims, the techniques of summarizing normal and pathological form that are generated should find immediate application in routine diagnosis and treatment of craniofacial birth defects from clefting through the synostoses. Geometrically, they all seem to be effectively characterized as anomalies of the ridge curve decomposition of the skull. The investigators propose to improve their systems for extracting geometric morphometric ridge-based measurements from skull surfaces and studying the statistics, i.e., means and variances of shape yielded by these methods. They will apply and test these methods on CT-imaged skulls from Apert's, Pfeiffer's and Crouzon's syndromes and on laser-scanned skin surfaces in regard to the repair of cleft lip and nose of children.