Optimal occlusion of teeth using planar structure information

Abstract

In orthodontics, occlusion is defined as the relationship between the upper and lower sets of teeth when the jaws are brought together. Understanding the nature of occlusion has important significance for the diagnosis and treatment of occlusal dysfunction and for planning reconstructive dentistry. The materials of study are 31 pairs of manually aligned dental study models. The upper and lower models are independently digitized using a laser surface scanner. Occlusion can be recovered by detecting and aligning a set of planes on the models. We describe a two-step procedure for determining the occlusal relationship using digitized dental models. The first step is a coarse alignment using four planar structures that are detected by K-means clustering, followed by principal component analysis. The second step is a refinement process using a variant of the iterative closest point technique. The quantitative results show that the algorithm is accurate, with an average measurement discrepancy of 0.74 mm between the physical and virtual models.