Efficient free-form surface representation with application in orthodontics

Orthodontics is the branch of dentistry concerned with the study of growth of the craniofacial complex. The detection and correction of malocclusion and other dental abnormalities is one of the most important and critical phases of orthodontic diagnosis. This paper introduces a system that can assist in automatic orthodontics diagnosis. The system can be used to classify skeletal and dental malocclusion from a limited number of measurements. This system is not intended to deal with severe cases but is aimed at cases more likely to be encountered in epidemiological studies. Prior to the measurement of the orthodontics parameters, the position of the teeth in the jaw model must be detected. Anew free-form surface representation is adopted for the efficient and accurate segmentation and separation of teeth from a scanned jaw model. The new representation encodes the curvature and surface normal information into a 2-D image. Image segmentation tools are then used to extract structures of high/low curvature. By iteratively removing these structures, individual teeth surfaces are obtained.