Facial bones segmentation from skull point clouds based on deviation angle

Facial bones segmentation is an important step to understanding a skull. In this paper, a method for segmenting facial bones from skull point clouds is proposed. The segmentation is based on the deviation angle features. The method consists of three phases: surface normal estimation, feature extraction, and point clouds classification. The method is applied to skull point clouds derived from computed tomography images. For evaluation, the method is compared with manual segmentation. The method has succeeded in segmenting facial bones with Precision 5 0.836, Recall 5 0.951, and F 5 0.890.