Image Segmentation Techniques Applied to Point Clouds of Dental Models with an Improvement in Semi-Automatic Teeth Segmentation

摘要

This paper presents an exploratory study on the application of a combination of different segmentation techniques to point clouds of dental models. The techniques are based in geometric primitives (e.g. RANSAC), region growing segmentation and graph theory (particularly the "Min-Cut" algorithm), and were tested using dental 3D point clouds. Data were acquired using a Konica Minolta Vivid 9i laser range scanner. Also, a semi-automatic segmentation methodology is presented. Results of teeth segmentation using testing data suggest that it is possible to automatically segment teeth from digital 3D models.