New Segmentation Approach to Extract Human Mandible Bones Based on Actual Computed Tomography Data

In this paper, a new approach for segmenting different anatomical reg ions in dental Computed Tomography (CT) studies is presented. The approach consists of three steps: Hounsfield unit's threshold (HU) based on gray-level segmentation, multi-object with textu re extraction and anatomical regions identification. First, a HU threshold window sets to separate between different regions upon their gray-level values; second, a set of objects are generated by and texture descriptors are calculated for selected windows from the image data sample. Finally, identification of different anatomical regions set for mandib le bones cortical and cancellous. It is expected that the proposed approach will also help automate different semi-automatic segmentation techniques by providing initial boundary points for deformable models or seed points for split and merge segmentation algorithms. Preliminary results obtained for dental CT studies of human-mandib le are presented.