Forensic facial approximation was applied to a 5000-year-old female skull from a shell midden in Guar Kepah, Malaysia. The skull was scanned using a computed tomography (CT) scanner in the Radiology Department of the Hospital Universiti Sains Malaysia using a Light Speed Plus scanner with a 1 mm section thickness in spiral mode and a 512 × 512 matrix. The resulting images were stored in Digital Imaging and Communications in Medicine (DICOM) format. A three-dimensional (3D) model of the skull was obtained from the CT scan data using Blender’s 3D modelling and animation software. After the skull was reconstructed, it was placed on the Frankfurt plane, and soft tissue thickness markers were placed based on 34 Malay CT scan data of the nose and lips. The technique based on facial approximation by data extracted from facial measurements of living individuals showed greater anatomical coherence when combined with anatomical deformation. The facial approximation in this study will pave the way towards understanding face prediction based on skull structures, soft tissue prediction rules, and soft tissue thickness descriptors.
Reconstructing a large skull defect is a challenge, as it normally involves the use of sophisticated proprietary image processing and expensive CAD software. As an alternative, open-source software can be used for this purpose. This study aimed to compare the 3D cranial implants reconstructed from computed tomography (CT) images using the open-source MITK software with commercial 3-matic software for ten decompressive craniectomy patients. The shape-based interpolation method was used, in which the technique of segmenting every fifth and tenth slice of CT data was performed. The final design of patient-specific implants from both software was exported to STL format for analysis. The results of the Kruskal–Wallis test for the surface and volume of cranial implants designed using 3-matic and the two MITK techniques showed no significant difference, p > 0.05. The results of the Hausdorff Distance (HD) and Dice Similarity Coefficient (DSC) analyses for cranial implants designed using 3-matic software and the two different MITK techniques showed that the average points distance for 3-matic versus MITK was 0.28 mm (every tenth slice) and 0.15 mm (every fifth slice), and the similarity between 3-matic and MITK on every tenth and fifth slices were 85.1% and 89.7%, respectively. The results also showed that the open-source MITK software is comparable with the commercial software for designing patient-specific implants.