Improved B-Spline Contour Fitting Using Genetic Algorithm for the Segmentation of Dental Computerized Tomography Image Sequences

摘要

In the dental field, 3D tooth modeling, in which each tooth can be manipulated individually, is an essential component of the simulation of orthodontic surgery and treatment. However, in dental computerized tomography slices teeth are located closely together or inside alveolar bone having an intensity similar to that of teeth. This makes it difficult to individually segment a tooth before building its 3D model. Conventional methods such as the global threshold and snake algorithms fail to accurately extract the boundary of each tooth. In this paper, we present an improved contour extraction algorithm based on B-spline contour fitting using genetic algorithm. We propose a new fitting function incorporating the gradient direction information on the fitting contour to prevent it from invading the areas of other teeth or alveolar bone. Furthermore, to speed up the convergence to the best solution we use a novel adaptive probability for crossover and mutation in the evolutionary program of the genetic algorithm. Segmentation results for real dental images demonstrate that our method can accurately determine the boundary for individual teeth as well as its 3D model while other methods fail. Independent manipulation of each tooth model demonstrates the practical usage of our method.