Details of Research Outputs

Purpose: Segmentation of the maxillary sinuses for three-dimensional (3D) reconstruction, visualization and volumetry is sought using an automated algorithm applied to cone beam computed tomographic (CBCT) data sets. Materials and Methods: Cone beam computed tomography (CBCT) data sets of three subjects aged 9, 17, and 27 were used in 3D segmentation and reconstruction. The maxillary sinuses were obtained by propagation from one start point in the right sinus and one start point in the left sinus to the whole regions of both sinuses. The procedure was based on voxel intensity distributions and common anatomic structures, specifically each middle meatus of the nasal cavity. A program was written in C++ and VTK languages to demonstrate the surface topological shapes of the maxillary sinuses. Results: The developed segmentation algorithm separated maxillary sinuses successfully permitting accurate comparisons. It was robust and efficient. 3D morphological features of the maxillary sinuses were observed from three human subjects. Conclusions: Automated segmentation of maxillary sinuses from CBCT data sets is feasible using the proposed method. This tool might be useful for visualization, pathological diagnosis, and treatment planning of maxillary sinus disorders. © CARS 2006.