A dense approach for computation of facial soft tissue thickness data

Abstract Objective The present study aims to propose a dense approach for computation of facial soft tissue thickness (FSTT) data. For this purpose, three-dimensional surface models of the skull and skin were generated from computed tomography (CT) data and all possible skull-to-face distances were calculated for each skull-skin pair. Material and methods The CT images were obtained using a Toshiba Aquilion64 CT system. Based on the scan data for each individual, surface models of the skull and skin were created in InVesalius. The produced models represented orientable irregular dense triangulated meshes with properly oriented outward-pointing normals. The model postprocessing was performed in MeshLab and as a result only the face region from the models was kept. The skull-to-face distances were computed in CloudCompare using the M3C2 plugin. Results The M3C2 plugin provides measurements perpendicular to the skull surface along the direction of the outward-pointing normal vectors of the triangulated mesh. The measurements originate only from the front skull surface since the distance calculations were restricted to the positive half-space relatively to the normal. The number of calculated distances amounts to over 70,000 per skull-skin pair. Conclusion The M3C2 plugin enables computation and visualization of dense data of FSTTs.