Craniofacial identification standards: A review of reliability, reproducibility, and implementation.

There are numerous anatomical and anthropometrical standards that can be utilised for craniofacial analysis and identification. These standards originate from a wide variety of sources, such as orthodontic, maxillofacial, surgical, anatomical, anthropological and forensic literature, and numerous media have been employed to collect data from living and deceased subjects. With the development of clinical imaging and the enhanced technology associated with this field, multiple methods of data collection have become accessible, including Computed Tomography, Cone-Beam Computed Tomography, Magnetic Resonance Imaging, Radiographs, Three-dimensional Scanning, Photogrammetry and Ultrasound, alongside the more traditional in vivo methods, such as palpation and direct measurement, and cadaveric human dissection. Practitioners often struggle to identify the most appropriate standards and research results are frequently inconsistent adding to the confusion. This paper aims to clarify how practitioners can choose optimal standards, which standards are the most reliable and when to apply these standards for craniofacial identification. This paper describes the advantages and disadvantages of each mode of data collection and collates published research to review standards across different populations for each facial feature. This paper does not aim to be a practical instruction paper; since this field encompasses a wide range of 2D and 3D approaches (e.g., clay sculpture, sketch, automated, computer-modelling), the implementation of these standards is left to the individual practitioner.

Digital 2D, 2.5D and 3D Methods for Adding Photo-Realistic Textures to 3D Facial Depictions of People from the Past.

Facial reconstruction is a technique that can be used to estimate individual faces from human skulls. The presentation of 3D facial reconstructions as photo-realistic depictions of people from the past to public audiences varies widely due to differing methods, the artists' CGI skillset, and access to VFX software required to generate plausible faces.This chapter describes three digital methods for the addition of realistic textures to 3D facial reconstructions; a 2D photo-composite method, a 3D digital painting and rendering method, and a previously undescribed hybrid 2.5D method.These methods are compared and discussed in relation to artistic proficiency, morphological accuracy and practitioner bias.

Mandibular shape prediction using cephalometric analysis: applications in craniofacial analysis, forensic anthropology and archaeological reconstruction.

BACKGROUND: The human mandible is variable in shape, size and position and any deviation from normal can affect the facial appearance and dental occlusion. OBJECTIVES: The objectives of this study were to determine whether the Sassouni cephalometric analysis could help predict two-dimensional mandibular shape in humans using cephalometric planes and landmarks. MATERIALS AND METHODS: A retrospective computerised analysis of 100 lateral cephalometric radiographs taken at Kingston Hospital Orthodontic Department was carried out. RESULTS: Results showed that the Euclidean straight-line mean difference between the estimated position of gonion and traced position of gonion was 7.89 mm and the Euclidean straight-line mean difference between the estimated position of pogonion and the traced position of pogonion was 11.15 mm. The length of the anterior cranial base as measured by sella-nasion was positively correlated with the length of the mandibular body gonion-menton, r = 0.381 and regression analysis showed the length of the anterior cranial base sella-nasion could be predictive of the length of the mandibular body gonion-menton by the equation 22.65 + 0.5426x, where x = length of the anterior cranial base (SN). There was a significant association with convex shaped palates and oblique shaped mandibles, p = 0.0004. CONCLUSIONS: The method described in this study can be used to help estimate the position of cephalometric points gonion and pogonion and thereby sagittal mandibular length. This method is more accurate in skeletal class I cases and therefore has potential applications in craniofacial anthropology and the 'missing mandible' problem in forensic and archaeological reconstruction.

A guided manual method for juvenile age progression using digital images.

Predicting the possible age-related changes to a child's face, age progression methods modify the shape, colour and texture of a facial image while retaining the identity of the individual. However, the techniques vary between different practitioners. This study combines different age progression techniques for juvenile subjects, various researches based on longitudinal radiographic data; physical anthropometric measurements of the head and face; and digital image measurements in pixels. Utilising 12 anthropometric measurements of the face, this study documents a new workflow for digital manual age progression. An inter-observer error study (n = 5) included the comparison of two age progressions of the same individual at different ages. The proposed age progression method recorded satisfactory levels of repeatability based on the 12 anthropometric measurements. Seven measurements achieved an error below 8.60%. Facial anthropometric measurements involving the nasion (n) and trichion (tr) showed the most inconsistency (14-34% difference between the practitioners). Overall, the horizontal measurements were more accurate than the vertical measurements. The age progression images were compared using a manual morphological method and machine-based face recognition. The confidence scores generated by the three different facial recognition APIs suggested the performance of any age progression not only varies between practitioners, but also between the Facial recognition systems. The suggested new workflow was able to guide the positioning of the facial features, but the process of age progression remains dependant on artistic interpretation.

Prediction of nasal morphology in facial reconstruction: Validation and recalibration of the Rynn method.

BACKGROUND: Prediction of the nose from the skull remains an important issue in forensic facial approximation. In 2010, Rynn et al. published a method of predicting nose projection from the skull. With this method, three craniometric measurements (x, y, z) are taken, and these are then used in regression formulae to estimate the nasal dimensions. AIM: The purpose of this study was to examine and test the accuracy of the Rynn et al. method and if necessary to adapt the formulae for this population. SUBJECTS AND METHODS: A sample of 90 CT scans of Turkish adults was used in the study. The actual and predicted dimensions were compared using t-test. The age of the individuals ranged from 20 to 40 years by sex. RESULTS: The descriptive statistics and correlations were calculated, and the actual and predicted measurements were compared. The differences between the actual and predicted values were statistically significant (p < 0.01), with -1 mm for males and -1.5 mm for females. Validation accuracies ranged from 76 to 92% in females and 72 to 82% in males. Recalibration equation accuracies ranged from 88 to 100% in females and 90 to 100% in males. CONCLUSION: The results showed that the recalibration of the Rynn et al. method and its formulae gave satisfactory results with less error and can be employed in facial approximation cases.

A regional method for craniofacial reconstruction based on coordinate adjustments and a new fusion strategy.

Craniofacial reconstruction recreates a facial outlook from the cranium based on the relationship between the face and the skull to assist identification. But craniofacial structures are very complex, and this relationship is not the same in different craniofacial regions. Several regional methods have recently been proposed, these methods segmented the face and skull into regions, and the relationship of each region is then learned independently, after that, facial regions for a given skull are estimated and finally glued together to generate a face. Most of these regional methods use vertex coordinates to represent the regions, and they define a uniform coordinate system for all of the regions. Consequently, the inconsistence in the positions of regions between different individuals is not eliminated before learning the relationships between the face and skull regions, and this reduces the accuracy of the craniofacial reconstruction. In order to solve this problem, an improved regional method is proposed in this paper involving two types of coordinate adjustments. One is the global coordinate adjustment performed on the skulls and faces with the purpose to eliminate the inconsistence of position and pose of the heads; the other is the local coordinate adjustment performed on the skull and face regions with the purpose to eliminate the inconsistence of position of these regions. After these two coordinate adjustments, partial least squares regression (PLSR) is used to estimate the relationship between the face region and the skull region. In order to obtain a more accurate reconstruction, a new fusion strategy is also proposed in the paper to maintain the reconstructed feature regions when gluing the facial regions together. This is based on the observation that the feature regions usually have less reconstruction errors compared to rest of the face. The results demonstrate that the coordinate adjustments and the new fusion strategy can significantly improve the craniofacial reconstructions.