A computerized facial approximation method for Homo sapiens based on facial soft tissue thickness depths and geometric morphometrics.

Facial approximation (FA) provides a promising means of generating the possible facial appearance of a deceased person. It facilitates exploration of the evolutionary forces driving anatomical changes in ancestral humans and can capture public attention. Despite the recent progress made toward improving the performance of FA methods, a limited understanding of detailed quantitative craniofacial relationships between facial bone and soft tissue morphology may hinder their accuracy, and hence subjective experience and artistic interpretation are required. In this study, we explored craniofacial relationships among human populations based upon average facial soft tissue thickness depths (FSTDs) and covariations between hard and soft tissues of the nose and mouth using geometric morphometrics. Furthermore, we proposed a computerized method to assign the learned craniofacial relationships to generate a probable facial appearance of Homo sapiens, reducing human intervention. A smaller resemblance comparison (an average Procrustes distance was 0.0258 and an average Euclidean distance was 1.79 mm) between approximated and actual faces and a greater recognition rate (91.67%) tested by a face pool indicated that average dense FSTDs contributed to raising the accuracy of approximated faces. Results of partial least squares (PLS) analysis showed that nasal and oral hard tissues have an effect on their soft tissues separately. However, relatively weaker RV correlations (<0.4) and greater approximation errors suggested that we need to be cautious about the accuracy of the approximated nose and mouth soft tissue shapes from bony structures. Overall, the proposed method can facilitate investigations of craniofacial relationships and potentially improve the reliability of the approximated faces for use in numerous applications in forensic science, archaeology, and anthropology.

The production of digital and printed resources from multiple modalities using visualization and three-dimensional printing techniques.

PURPOSE: Virtual digital resources and printed models have become indispensable tools for medical training and surgical planning. Nevertheless, printed models of soft tissue organs are still challenging to reproduce. This study adopts open source packages and a low-cost desktop 3D printer to convert multiple modalities of medical images to digital resources (volume rendering images and digital models) and lifelike printed models, which are useful to enhance our understanding of the geometric structure and complex spatial nature of anatomical organs. MATERIALS AND METHODS: Neuroimaging technologies such as CT, CTA, MRI, and TOF-MRA collect serial medical images. The procedures for producing digital resources can be divided into volume rendering and medical image reconstruction. To verify the accuracy of reconstruction, this study presents qualitative and quantitative assessments. Subsequently, digital models are archived as stereolithography format files and imported to the bundled software of the 3D printer. The printed models are produced using polylactide filament materials. RESULTS: We have successfully converted multiple modalities of medical images to digital resources and printed models for both hard organs (cranial base and tooth) and soft tissue organs (brain, blood vessels of the brain, the heart chambers and vessel lumen, and pituitary tumor). Multiple digital resources and printed models were provided to illustrate the anatomical relationship between organs and complicated surrounding structures. Three-dimensional printing (3DP) is a powerful tool to produce lifelike and tangible models. CONCLUSIONS: We present an available and cost-effective method for producing both digital resources and printed models. The choice of modality in medical images and the processing approach is important when reproducing soft tissue organs models. The accuracy of the printed model is determined by the quality of organ models and 3DP. With the ongoing improvement of printing techniques and the variety of materials available, 3DP will become an indispensable tool in medical training and surgical planning.