Computerized craniofacial reconstruction: Conceptual framework and review

Deep Learning-Based Facial and Skeletal Transformations for Surgical Planning

The increasing application of virtual surgical planning (VSP) in orthognathic surgery implies a critical need for accurate prediction of facial and skeletal shapes. The craniofacial relationship in patients with dentofacial deformities is still not understood, and transformations between facial and skeletal shapes remain a challenging task due to intricate anatomical structures and nonlinear relationships between the facial soft tissue and bones. In this study, a novel bidirectional 3-dimensional (3D) deep learning framework, named P2P-ConvGC, was developed and validated based on a large-scale data set for accurate subject-specific transformations between facial and skeletal shapes. Specifically, the 2-stage point-sampling strategy was used to generate multiple nonoverlapping point subsets to represent high-resolution facial and skeletal shapes. Facial and skeletal point subsets were separately input into the prediction system to predict the corresponding skeletal and facial point subsets via the skeletal prediction subnetwork and facial prediction subnetwork. For quantitative evaluation, the accuracy was calculated with shape errors and landmark errors between the predicted skeleton or face with corresponding ground truths. The shape error was calculated by comparing the predicted point sets with the ground truths, with P2P-ConvGC outperforming existing state-of-the-art algorithms including P2P-Net, P2P-ASNL, and P2P-Conv. The total landmark errors (Euclidean distances of craniomaxillofacial landmarks) of P2P-ConvGC in the upper skull, mandible, and facial soft tissues were 1.964 ± 0.904 mm, 2.398 ± 1.174 mm, and 2.226 ± 0.774 mm, respectively. Furthermore, the clinical feasibility of the bidirectional model was validated using a clinical cohort. The result demonstrated its prediction ability with average surface deviation errors of 0.895 ± 0.175 mm for facial prediction and 0.906 ± 0.082 mm for skeletal prediction. To conclude, our proposed model achieved good performance on the subject-specific prediction of facial and skeletal shapes and showed clinical application potential in postoperative facial prediction and VSP for orthognathic surgery.

Automated reconstruction: Predictive models based on facial morphology matrices

Forensic Facial Approximation (FFA) has evolved, with techniques advancing to refine the intercorrelation between the soft-tissue facial profile and the underlying skull. FFA has become essential for identifying unknown persons in South Africa, where the high number of migrant and illegal labourers and many unidentified remains make the identification process challenging. However, existing FFA methods are based on American or European standards, rendering them inapplicable in a South African context. We addressed this issue by conducting a study to create prediction models based on the relationships between facial morphology and known factors, such as population affinity, sex, and age, in white South African and French samples. We retrospectively collected 184 adult cone beam computed tomography (CBCT) scans representing 76 white South Africans (29 males and 47 females) and 108 French nationals (54 males and 54 females) to develop predictive statistical models using a projection onto latent structures regression algorithm (PLSR). On training and untrained datasets, the accuracy of the estimated soft-tissue shape of the ears, eyes, nose, and mouth was measured using metric deviations. The predictive models were optimized by integrating additional variables such as sex and age. Based on trained data, the prediction errors for the ears, eyes, nose, and mouth ranged between 1.6 mm and 4.1 mm for white South Africans; for the French group, they ranged between 1.9 mm and 4.2 mm. Prediction errors on non-trained data ranged between 1.6 mm and 4.3 mm for white South Africans, whereas prediction errors ranging between 1.8 mm and 4.3 mm were observed for the French. Ultimately, our study provided promising predictive models. Although the statistical models can be improved, the inherent variability among individuals restricts the accuracy of FFA. The predictive validity of the models was improved by including sex and age variables and considering population affinity. By integrating these factors, more customized and accurate predictive models can be developed, ultimately strengthening the effectiveness of forensic analysis in the South African region.

Digitalization in Cranial Reconstruction: Revolutionizing Precision and Innovation

Cranioplasty for cranial defects can be complex and challenging in composite defects. The intricate 3D structure of the craniofacial skeleton poses various difficulties encountered in surgical reconstruction. The continuous progress in computer-aided design and computer-aided manufacturing design, and fabrication technology has led to a growing array of applications for visual analog scale and 3D printing in craniofacial surgery, encompassing preoperative assessment, the creation of cutting guides, and the development of custom implants and stereolithographic models. Within this review, the authors detail the present and developing applications of virtual surgical planning, 3D bioprinting, augmented reality, and virtual reality in craniofacial reconstruction.

Average Three-Dimensional Skeletofacial Model as a Template for Bone Repositioning during Virtual Orthognathic Surgery

BACKGROUND

Virtual planning has revolutionized orthognathic surgery. This study presents a computer-assisted method for constructing average three-dimensional skeletofacial models that can be applied as templates for surgical planning for maxillomandibular repositioning.

METHODS

The authors used the images of 60 individuals (30 women and 30 men) who had never undergone orthognathic surgery to construct an average three-dimensional skeletofacial model for male participants and one for female participants. The authors validated the accuracy of the newly developed skeletofacial models by comparing their images with 30 surgical simulation images (ie, skulls) that had been created using three-dimensional cephalometric normative data. The comparison was conducted by superimposing surgical simulation images created using the authors' models with the previously created images to analyze their differences, particularly differences in the jawbone position.

RESULTS

For all participants, the authors compared the jaw position in the surgical simulation images created using the authors' average three-dimensional skeletofacial models with that in the images created using three-dimensional cephalometric normative data. The results revealed that the planned maxillary and mandibular positions were similar in both images and that the differences between all facial landmarks were less than 1 mm, except for one dental position. Most studies have reported less than 2 mm to be the success criterion for the distance difference between planned and outcome images; thus, the authors' data indicate high consistency between the images in terms of jawbone position.

CONCLUSION

The authors' average three-dimensional skeletofacial models provide an innovative template-assisted orthognathic surgery planning modality that can enhance the fully digital workflow for virtual orthognathic surgical planning.

CLINICAL QUESTION/LEVEL OF EVIDENCE

Therapeutic, V.

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.

Protocol for capturing 3D facial meshes for rhinoseptoplasty planning

OBJECTIVES

To present and execute a protocol for the capture of 3D facial images using photogrammetry through the open access software Blender and its add-on OrtogOnBlender (OOB) and to evaluate the compatibility of the 3D meshes generated with Computed tomography (CT) of the sinuses.

METHODS

Individuals >18 years old, candidates for Rhinoseptoplasty in a tertiary hospital, were submitted to a photographic session to perform the standardized protocol. In the session, divided into 3 phases, sequential photos were taken for processing the photogrammetry in the OOB and producing 3D meshes of the face. The photogrammetry reconstructions were compared with the reference mesh of the soft tissue surface of the Sinus CT scan to assess compatibility between them.

RESULTS

21 patients were included, 67% female. 3 photogrammetry meshes and 1 CT reference mesh were generated, which demonstrated matching compatibility, as most of the mean distances between cloud points were <1.48 mm. Phase 3 of the session with the highest number of photos (54.36 ± 15.05) generated the most satisfactory mesh with the best resolution.

CONCLUSIONS

The proposed protocol is reproducible and feasible in clinical practice, generated satisfactory 3D meshes of the face, being a potential tool for surgical planning and comparison of results. For the implementation of photogrammetry for use in 3D anthropometry, it is necessary to validate this method.

LEVEL OF EVIDENCE: 3

OCEBM Levels of Evidence Working Group.1 "The Oxford 2011 Levels of Evidence". Oxford Centre for Evidence-Based Medicine. http://www.cebm.net/index.aspx?o=5653.

Facial reconstruction using 3-D computerized method: A scoping review of Methods, current Status, and future developments

Facial reconstruction (otherwise known as facial approximation) is an alternative method that has been widely accepted in forensic anthropological and archaeological circumstances. This method is considered useful for creating the virtual face of a person based on skull remain. Three-dimensional (3-D) traditional facial reconstruction (known as sculpture or manual method) has been recognized for more than a century; however, it was declared to be subjective and required anthropological training. Until recently, with the progression of computational technologies, many studies attempted to develop a more appropriate method, so-called the 3-D computerized facial reconstruction. This method also relied on anatomical knowledge of the face-skull relationship, divided into semi- and automated based computational method. The 3-D computerized facial reconstruction makes it more rapid, more flexible, and more realistic to generate multiple representations of faces. Moreover, new tools and technology are continuously generating fascinating and sound research as well as encouraging multidisciplinary collaboration. This has led to a paradigm shift in the 3-D computerized facial reconstruction to a new finding and new technique based on artificial intelligence in academia. Based on the last 10-years scientific-published documents, this article aims to explain the overview of the 3-D computerized facial reconstruction and progression as well as an issue relating to future directions to encourage further improvement.

Advancement in Human Face Prediction Using DNA

The rapid improvements in identifying the genetic factors contributing to facial morphology have enabled the early identification of craniofacial syndromes. Similarly, this technology can be vital in forensic cases involving human identification from biological traces or human remains, especially when reference samples are not available in the deoxyribose nucleic acid (DNA) database. This review summarizes the currently used methods for predicting human phenotypes such as age, ancestry, pigmentation, and facial features based on genetic variations. To identify the facial features affected by DNA, various two-dimensional (2D)- and three-dimensional (3D)-scanning techniques and analysis tools are reviewed. A comparison between the scanning technologies is also presented in this review. Face-landmarking techniques and face-phenotyping algorithms are discussed in chronological order. Then, the latest approaches in genetic to 3D face shape analysis are emphasized. A systematic review of the current markers that passed the threshold of a genome-wide association (GWAS) of single nucleotide polymorphism (SNP)-face traits from the GWAS Catalog is also provided using the preferred reporting items for systematic reviews and meta-analyses (PRISMA), approach. Finally, the current challenges in forensic DNA phenotyping are analyzed and discussed.

Reinforcement learning coupled with finite element modeling for facial motion learning

BACKGROUND AND OBJECTIVE

Facial palsy patients or patients with facial transplantation have abnormal facial motion due to altered facial muscle functions and nerve damage. Computer-aided system and physics-based models have been developed to provide objective and quantitative information. However, the predictive capacity of these solutions is still limited to explore the facial motion patterns with emerging properties. The present study aims to couple the reinforcement learning and the finite element modeling for facial motion learning and prediction.

METHODS

A novel modeling workflow for learning facial motion was developed. A physically-based model of the face within the Artisynth modeling platform was used. Information exchange protocol was proposed to link reinforcement learning and rigid multi-bodies dynamics outcomes. Two reinforcement learning algorithms (deep deterministic policy gradient (DDPG) and Twin-delayed DDPG (TD3)) were used and implemented to drive the simulations of symmetry-oriented and smile movements. Numerical outcomes were compared to experimental observations (Bosphorus database) for evaluation and validation purposes.

RESULTS

As result, after more than 100 episodes of exploring the environment, the agent starts to learn from previous trials and can find the optimal policy after more than 300 episodes of training. Regarding the symmetry-oriented motion, the muscle excitations predicted by the trained agent help to increase the value of reward from R = -2.06 to R = -0.23, which counts for ∼89% improvement of the symmetry value of the face. For smile-oriented motion, two points at the edge of the mouth move up 0.35 cm, which is within the range of movements estimated from the Bosphorus database (0.4 ± 0.32 cm).

CONCLUSIONS

The present study explored the muscle excitation patterns by coupling reinforcement learning with a detailed finite element model of the face. We developed, for the first time, a novel coupling scheme to integrate the finite element simulation into the reinforcement learning process for facial motion learning. As perspectives, this present workflow will be applied for facial palsy and facial transplantation patients to guide and optimize the functional rehabilitation program.

The development and testing of Thai facial soft tissue thickness data in three-dimensional computerized forensic facial reconstruction

Forensic facial reconstruction is a useful tool to assist the public in recognizing human remains, leading to positive forensic investigation outcomes. To reproduce a virtual face, facial soft tissue thickness is one of the major guidelines to reach the accuracy and reliability for three-dimensional computerized facial reconstruction, a method that is making a significant contribution to improving forensic investigation and identification. This study aimed to develop a facial soft tissue thickness dataset for a Thai population, and test its reliability in the context of facial reconstruction. Three-dimensional facial reconstruction was conducted on four skulls (2 males and 2 females, with ages ranging between 51 to 60 years). Two main tools of three-dimensional computer animation and modeling software-Blender and Autodesk Maya-were used to rebuild the three-dimensional virtual face. The three-dimensional coordinate (x, y, z) cutaneous landmarks on the mesh templates were aligned homologous to the facial soft tissue thickness markers on the three-dimensional skull model. The final three-dimensional virtual face was compared to the target frontal photograph using face pool comparison. Four three-dimensional virtual faces were matched at low to moderate levels, ranging from 30% to 70% accuracy. These results demonstrate that the facial soft tissue thickness database of a Thai population applied in this study could be useful for three-dimensional computerized facial reconstruction purposes.

Enhanced head-skull shape learning using statistical modeling and topological features

Skull prediction from the head is a challenging issue toward a cost-effective therapeutic solution for facial disorders. This issue was initially studied in our previous work using full head-to-skull relationship learning. However, the head-skull thickness topology is locally shaped, especially in the face region. Thus, the objective of the present study was to enhance our head-to-skull prediction problem by using local topological features for training and predicting. Head and skull feature points were sampled on 329 head and skull models from computed tomography (CT) images. These feature points were classified into the back and facial topologies. Head-to-skull relations were trained using the partial least square regression (PLSR) models separately in the two topologies. A hyperparameter tuning process was also conducted for selecting optimal parameters for each training model. Thus, a new skull could be generated so that its shape was statistically fitted with the target head. Mean errors of the predicted skulls using the topology-based learning method were better than those using the non-topology-based learning method. After tenfold cross-validation, the mean error was enhanced 36.96% for the skull shapes and 14.17% for the skull models. Mean error in the facial skull region was especially improved with 4.98%. The mean errors were also improved 11.71% and 25.74% in the muscle attachment regions and the back skull regions respectively. Moreover, using the enhanced learning strategy, the errors (mean ± SD) for the best and worst prediction cases are from 1.1994 ± 1.1225 mm (median: 0.9036, coefficient of multiple determination (R²): 0.997274) to 3.6972 ± 2.4118 mm (median: 3.9089, R²: 0.999614) and from 2.0172 ± 2.0454 mm (median: 1.2999, R²: 0.995959) to 4.0227 ± 2.6098 mm (median: 3.9998, R²: 0.998577) for the predicted skull shapes and the predicted skull models respectively. This present study showed that more detailed information on the head-skull shape leads to a better accuracy level for the skull prediction from the head. In particular, local topological features on the back and face regions of interest should be considered toward a better learning strategy for the head-to-skull prediction problem. In perspective, this enhanced learning strategy was used to update our developed clinical decision support system for facial disorders. Furthermore, a new class of learning methods, called geometric deep learning will be studied.

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.

Forensic Recreation and Visual Representation of Greek Orthodox Church Saint Eftychios of Crete

Facial reconstruction is employed in medical science and archaeology. Though quite popular as anthropological method, it has not so far been used in the orthodox ecclesiastical tradition. This work presents the facial reconstruction of St Eftychios of Crete, who lived between the ninth and tenth centuries. Computed tomography and reverse engineering methods were employed to complete the task. Reconstruction of the mandible and the missing left zygomatic arch was implemented following the Sassouni method. The American method was followed for the soft tissues, with clay deposition of appropriate thickness, on the surface of the skull model. The eyes, nose, and lips were added based on the dimensions of the underlying bone structures. Long hair and beard were added, according to the classic Byzantine tradition pattern of the time period. The final bust developed was then digitized, using a 3D non-contact laser scanner. The 3D geometry produced was employed to produce a mold with vacuum casting techniques. This mold provides the ability to produce copies of the bust, if needed. At the same time, a realistic 3D representation of the Saint's bust was developed, with the aid of special software, in order to compare the traditional forensic reconstruction to the pure digital one. This work is the first case of a Saint's facial reconstruction in the Orthodox Church. The facial reconstruction process, with all the limitations considered, offers the ability to present a realistic aspect of a Greek Orthodox Church Saint, in a form that is easily accessible. Both physical and digital facial reconstruction processes were based on scientific data, so they were as accurate as possible, considering that the mandible was missing in the skull. The facial reconstruction was entirely implemented in Greece creating the basis for similar work in the future. The final bust developed was donated to the Odigitria Monastery, to be exhibited to its visitors.

Kinect-driven Patient-specific Head, Skull, and Muscle Network Modelling for Facial Palsy Patients

BACKGROUND AND OBJECTIVE

Facial palsy negatively affects both professional and personal life qualities of involved patients. Classical facial rehabilitation strategies can recover facial mimics into their normal and symmetrical movements and appearances. However, there is a lack of objective, quantitative, and in-vivo facial texture and muscle activation bio-feedbacks for personalizing rehabilitation programs and diagnosing recovering progresses. Consequently, this study proposed a novel patient-specific modelling method for generating a full patient specific head model from a visual sensor and then computing the facial texture and muscle activation in real-time for further clinical decision making.

METHODS

The modeling workflow includes (1) Kinect-to-head, (2) head-to-skull, and (3) muscle network definition & generation processes. In the Kinect-to-head process, subject-specific data acquired from a new user in neutral mimic were used for generating his/her geometrical head model with facial texture. In particular, a template head model was deformed to optimally fit with high-definition facial points acquired by the Kinect sensor. Moreover, the facial texture was also merged from his/her facial images in left, right, and center points of view. In the head-to-skull process, a generic skull model was deformed so that its shape was statistically fitted with his/her geometrical head model. In the muscle network definition & generation process, a muscle network was defined from the head and skull models for computing muscle strains during facial movements. Muscle insertion points and muscle attachment points were defined as vertex positions on the head model and the skull model respectively based on the standard facial anatomy. Three healthy subjects and two facial palsy patients were selected for validating the proposed method. In neutral positions, magnetic resonance imaging (MRI)-based head and skull models were compared with Kinect-based head and skull models. In mimic positions, infrared depth-based head models in smiling and [u]-pronouncing mimics were compared with appropriate animated Kinect-driven head models. The Hausdorff distance metric was used for these comparisons. Moreover, computed muscle lengths and strains in the tested facial mimics were validated with reported values in literature.

RESULTS

With the current hardware configuration, the patient-specific head model with skull and muscle network could be fast generated within 17.16±0.37s and animated in real-time with the framerate of 40 fps. In neutral positions, the best mean error was 1.91 mm for the head models and 3.21 mm for the skull models. On facial regions, the best mean errors were 1.53 mm and 2.82 mm for head and skull models respectively. On muscle insertion/attachment point regions, the best mean errors were 1.09 mm and 2.16 mm for head and skull models respectively. In mimic positions, these errors were 2.02 mm in smiling mimics and 2.00 mm in [u]-pronouncing mimics for the head models on facial regions. All above error values were computed on a one-time validation procedure. Facial muscles exhibited muscle shortening and muscle elongating for smiling and pronunciation of sound [u] respectively. Extracted muscle features (i.e. muscle length and strain) are in agreement with experimental and literature data.

CONCLUSIONS

This study proposed a novel modeling method for fast generating and animating patient-specific biomechanical head model with facial texture and muscle activation bio-feedbacks. The Kinect-driven muscle strains could be applied for further real-time muscle-oriented facial paralysis grading and other facial analysis applications.

A revised nose tip shape validation method for facial reconstruction based on CT data from a modern German population

Several methods aid with reconstructing features of the human nose, including angle, projection and width, but only one study by Davy-Jow et al. (2012) has focused on nose tip shape. The main finding was that the shape of the nasal bridge is consistent with the shape of the nose tip. The study also theorised that the method would not be suitable for snub (upturned) noses. Although promising, further investigation with a larger sample of different origin would be of benefit. In addition, grouping samples into upturned, horizontal and downturned nose tips could reveal the need for a difference in the applied method. The approach has been recreated with a larger sample size (N = 103 versus N = 25) derived from a modern German population. Based on soft tissue models, the individuals were firstly grouped into three categories; upturned, horizontal, and downturned noses. Computed Tomography (CT) data allowed the simultaneous visualisation of both skull and (semi-transparent) facial surfaces. Each head was viewed frontally in the Frankfurt Horizontal Plane (FHP), and then tilted back until the nasal tip superimposed the nasal bridge, with the angle of tilt measured from the FHP. The results show that the angle of tilt is significantly different for upturned, horizontal, and downturned noses, but that it can be equally applied to all three groups. The mean angle was 44° for upturned noses, 51° for horizontal, and 56° for downturned. Error studies suggest a very high accuracy and repeatability with intra-class correlation coefficients of 0.991 (inter-observer error) and 0.972 (intra-observer error) respectively.

Facial soft tissue thickness differences among different vertical facial patterns

In forensic facial approximation, facial soft tissue thickness (FSTT) measurements play a major role. These values are affected by many factors such as ethnicity, age and sex, in addition to measurement errors. We hypothesize that an additional source of error is the lack of consideration of facial type in the assessment of FSTT norms. The purpose of this study was to: 1- evaluate the presence of significant effects of vertical facial type within the FSTT measurements in adults and 2- assess the correlations between FSTT and hard and soft tissue cephalometric measurements. The sample consisted of the lateral cephalometric radiographs of 222 adult individuals (87 males; 135 females, 23.49±6.24 years of age) with normal occlusion and balanced profiles. Hard and soft tissue cephalometric measurements were taken, in addition to FSST at 10 facial landmarks. The sample was categorized into 3 vertical pattern groups based on the MP/SN angle: hypodivergent, normodivergent and hyperdivergent. Statistical analyses included MANOVA test and Pearson moment product for associations among variables. Statistically significant effect of vertical divergence on FSTT values was limited to the levels of Stomion, Labiomentale and Pogonion and FSTT measurements were associated with measurements related to the lower face (Lm and Pog) Moderate to high correlations between mandibular length and ramus length and FSTT values related to the lower face (LL, Lm and Pog mainly) emphasize further the important role of the underlying skeleton.

Nose approximation among South African groups from cone-beam computed tomography (CBCT) using a new computer-assisted method based on automatic landmarking

Considering the high demand for the identification of unknown remains in South Africa, a need exists to establish reliable facial approximation techniques that will take into account sex and age and, most importantly, be useful within the South African context. This study aimed to provide accurate statistical models for predicting nasal soft-tissue shape from information about the underlying skull subtract among a South African sample. The database containing 200 cone-beam computer tomography (CBCT) scans (100 black South Africans and 100 white South Africans). The acquisition and extraction of the 3D relevant anatomical structures (hard- and soft-tissue) were performed by an automated three-dimensional (3D) method based on an automatic dense landmarking procedure using MeVisLab © v. 2.7.1 software. An evaluation of shape differences attributed to known factors (ancestry, sex, size, and age) was performed using geometric morphometric and statistical models of prediction were created using a Projection onto Latent Structures Regression (PLSR) algorithm. The accuracy of the estimated soft-tissue nose was evaluated in terms of metric deviations on training and un-trained datasets. Our findings demonstrated the influence of factors (sex, aging, and allometry) on the variability of the hard- and soft-tissue among two South African population groups. This research provides accurate statistical models optimized by including additional information such as ancestry, sex, and age. When using the landmark-to landmark distances, the prediction errors ranged between 1.769mm and 2.164mm for black South Africans at the tip of the nose and the alae, while they ranged from 2.068mm to 2.175mm for the white subsample. The prediction errors on un-trained data were slightly larger, ranging between 2.139mm and 2.833mm for the black South African sample at the tip of the nose and the alae and ranging from 2.575mm to 2.859mm for the white South African sample. This research demonstrates the utilization of an automated 3Dmethod based on an automatic landmarking method as a convenient prerequisite for providing a valid and reliable nose prediction model that meets population-specific standards for South Africans.

Automatic landmarking as a convenient prerequisite for geometric morphometrics. Validation on cone beam computed tomography (CBCT)- based shape analysis of the nasal complex

Manual landmarking is used in several manual and semi-automated prediction guidelines for approximation of the nose. The manual placement of landmarks may, however, render the analysis less repeatable due to observer subjectivity and, consequently, have an impact on the accuracy of the human facial approximation. In order to address this subjectivity and thereby improve facial approximations, we are developing an automated three-dimensional (3D) method based on an automatic dense landmarking procedure using non-rigid surface registration. The aim of this study was to validate the automatic landmarking method by comparing the intra-observer errors (INTRA-OE) and inter-observer errors (INTER-OE) between automatic and manual landmarking. Cone beam computed tomography (CBCT) scans of adult South Africans were selected from the Oral and Dental Hospital, University of Pretoria, South Africa. In this study, the validation of the automatic landmarking was performed on 20 3D surfaces. INTRA-OE and INTER-OE were analyzed by registering 41 craniometric landmarks from 10 hard-tissue surfaces and 21 capulometric landmarks from 10 soft-tissue surfaces of the same individuals. Absolute precision of the landmark positioning (both on the samples as well as the template) was assessed by calculating the measurement error (ME) for each landmark over different observers. Systematic error (bias) and relative random error (precision) was further quantified through repeated measures ANOVA (ANOVA-RM). The analysis showed that the random component of the ME in landmark positioning between the automatic observations were on average on par with the manual observations, except for the soft-tissue landmarks where automatic landmarking showed lower ME compared to manual landmarking. No bias was observed within the craniometric landmarking methods, but some bias was observed for capulometric landmarking. In conclusion, this research provides a first validation of the precision and accuracy of the automatic placement of landmarks on 3D hard- and soft-tissue surfaces and demonstrates its utilization as a convenient prerequisite for geometric morphometrics based shape analysis of the nasal complex.

The masks of Lorenzo Tenchini: their anatomy and surgical/bioengineering clues

An academic, anatomist, and Lombrosian psychiatrist active at the University of Parma in Italy at the end of the 19th century, Lorenzo Tenchini produced ceroplastic-like masks that are unique in the anatomical Western context. These were prepared from 1885 to 1893 with the aim of 'cataloguing' the behaviour of prison inmates and psychiatric patients based on their facial surface anatomy. Due to the lack of any reference to the procedure used to prepare the masks, studies were undertaken by our group using X-ray scans, infrared spectroscopy, bioptic sampling, and microscopy analysis of the mask constituents. Results showed that the masks were stratified structures including plaster, cotton gauze/human epidermis, and wax, leading to a fabrication procedure reminiscent of 'additive layer manufacturing'. Differences in the depths of these layers were observed in relation to the facial contours, suggesting an attempt to reproduce, at least partially, the three-dimensional features of the facial soft tissues. We conclude the Tenchini masks are the first historical antecedent of the experimental method for face reconstruction used in the early 2000s to test the feasibility of transferring a complete strip of face and scalp from a deceased donor to a living recipient, in preparation for a complete face transplant. In addition, the layering procedure adopted conceptually mimics that developed only in the late 20th century for computer-aided rapid prototyping, and recently applied to bioengineering with biomaterials for a number of human structures including parts of the skull and face. Finally, the masks are a relevant example of mixed ceroplastic-cutaneous preparations in the history of anatomical research for clinical purposes.

Facial soft tissue thicknesses in craniofacial identification: Data collection protocols and associated measurement errors

Facial soft tissue thicknesses (FSTT) form a key component of craniofacial identification methods, but as for any data, embedded measurement errors are highly pertinent. These in part dictate the effective resolution of the measurements. As herein reviewed, measurement methods are highly varied in FSTT studies and associated measurement errors have generally not been paid much attention. Less than half (44%) of 95 FSTT studies comment on measurement error and not all of these provide specific quantification. Where informative error measurement protocols are employed (5% of studies), the mean error magnitudes range from 3% to 45% rTEM and are typically in the order of 10-20%. These values demonstrate that FSTT measurement errors are similar in size to (and likely larger than) the magnitudes of many biological effects being chased. As a result, the attribution of small millimeter or submillimeter differences in FSTT to biological variables must be undertaken with caution, especially where they have not been repeated across different studies/samples. To improve the integrity of FSTT studies and the reporting of FSTT measurement errors, we propose the following standard: (1) calculate the technical error of measurement (TEM or rTEM) in any FSTT research work; (2) assess the error embedded in the full data collection procedure; and (3) conduct validation testing of FSTT means proposed for point estimation prior to publication to ensure newly calculated FSTT means provide improvements. In order to facilitate the latter, a freely available R tool TDValidator that uses the C-Table data for validation testing is provided.

An average three-dimensional virtual human skull for a template-assisted maxillofacial surgery

INTRODUCTION

Although many advances have been made in three-dimensional virtual planning in maxillofacial surgery, facial harmony is still difficult to achieve and is heavily dependent on the surgeon's experience. The aim of the study is to present a method to build up an average three-dimensional virtual human skull to be used as a reference template for bone repositioning and reconstruction during maxillofacial surgical interventions.

METHODS

A total of 20 patients (10 females and 10 males) were selected for the optimal outcome after orthognathic surgery. Postoperative cone-beam computed tomography scans were collected and processed in order to obtain three-dimensional digital models of each skull. For male and female subgroups, the three-dimensional skull models were registered and an average three-dimensional virtual skull model was computed. Deviation color maps were calculated to show differences between each postoperative skull model in the population and the obtained average three-dimensional skull. A clinical use case of genioplasty treatment assisted by the provided average three-dimensional skull template was presented.

RESULTS

The overall mean deviation from the average three-dimensional skull model was 1.3 ± 0.6 and 1.6 ± 0.5 mm in male and female subgroups, respectively. For both groups, the greatest deviations were at the area of the mandible, while almost no deviation was found at the zygomatic and orbital areas. In the presented use case, the female average three-dimensional skull model was effectively used for guiding surgical planning.

CONCLUSION

The presented method of obtaining an average three-dimensional virtual human skull may offer the interesting perspective of performing an innovative template-assisted maxillofacial surgery.

Whole-exome sequencing identified four loci influencing craniofacial morphology in northern Han Chinese

Facial shape differences are one of the most significant phenotypes in humans. It is affected largely by skull shape. However, research into the genetic basis of the craniofacial morphology has rarely been reported. The present study aimed to identify genetic variants influencing craniofacial morphology in northern Han Chinese through whole-exome sequencing (WES). Phenotypic data of the volunteers’ faces and skulls were obtained through three-dimensional CT scan of the skull. A total of 48 phenotypes (35 facial and 13 cranial phenotypes) were used for the bioinformatics analysis. Four genetic loci were identified affecting the craniofacial shapes. The four candidate genes are RGPD3, IGSF3, SLC28A3, and USP40. Four single-nucleotide polymorphism (SNP) site mutations in RGPD3, IGSF3, and USP40 were significantly associated with the skull shape (p < 1×10⁻⁶), and three SNP site mutations in RGPD3, IGSF3, and SLC28A3 were significantly associated with the facial shape (p < 1×10⁻⁶). The rs62152530 site mutation in the RGPD3 gene may be closely associated with the nasal length, ear length, and alar width. The rs647711 site mutation in the IGSF3 gene may be closely associated with the nasal length, mandibular width, and width between the mental foramina. The rs10868138 site mutation in the SLC28A3 gene may be associated with the nasal length, alar width, width between tragus, and width between the mental foramina. The rs1048603 and rs838543 site mutations in the USP40 gene may be closely associated with the pyriform aperture width. Our findings provide useful genetic information for the determination of face morphology.

The Affordances of 3D and 4D Digital Technologies for Computerized Facial Depiction

3D digital technologies have advanced rapidly over recent decades and they can now afford new ways of interacting with anatomical and cultural artefacts. Such technologies allow for interactive investigation of visible or non-observable surfaces, haptic generation of content and tactile experiences with digital and physical representations. These interactions and technical advances often facilitate the generation of new knowledge through interdisciplinary and sympathetic approaches.Scientific and public understanding of anatomy are often enhanced by clinical imaging technologies, 3D surface scanning techniques, 3D haptic modelling methods and 3D fabrication systems. These digital and haptic technologies are seen as non-invasive and allow scientists, artists and the public to become active investigators in the visualisation of, and interaction with, human anatomy, remains and histories.Face Lab is a Liverpool John Moores University research group that focuses on creative digital face research; specifically the further development of a 3D computerized craniofacial depiction system, utilizing 3D digital technologies in facial analysis and identification of human remains for forensic investigation, or historical figures for archaeological interpretation.This chapter explores the affordances of such interactions for the non-destructive production of craniofacial depiction, through a case-study based exploration of Face Lab workflow.

Stereophotogrammetric analysis of labial morphology in a young adult Middle-Eastern population

INTRODUCTION

The majority of previous research delineating the morphological characteristics of the orolabial region has been on Caucasian populations, with very minor research on Mediterranean populations, and none on the Lebanese population.

AIM

The primary aim was to collect information on the gender-specific 3D morphology of the mouth and lips in young Middle Eastern adults. The secondary aim was to explore the presence of associations between orolabial morphology and age and body mass index (BMI), and to assess correlations between linear orolabial dimensions and area/volume measures.

METHODS

The study used non-invasive stereophotogrammetry to collect information on gender-specific 3D labial morphology (linear distances, areas, and volumes) for 122 adult Lebanese subjects, aged 18-30 years (47 males, 75 females). Associations between labial morphology and age and body mass index were assessed, in addition to correlations between linear orolabial dimensions and area/volume measures.

RESULTS

All linear, angular, area, and volume lip measurements displayed significant variability. Both lip area and volume were smaller in the upper than in the lower lip. Eighteen out of the 20 linear measurements were significantly larger in males. The ratio, area, and volume measurements mostly displayed no statistically significant gender dimorphism.

CONCLUSIONS

Alongside presenting the first documented report on anthropometric labial measurements of a young Lebanese adult population, this research highlights the presence of gender dimorphism in linear and angular measurements, but not in area and volume measurements, and a strong association between certain linear labial measurements and lip area and volume. In addition, it presents pilot data on the association between labial anthropometry and body mass index.

Midsagittal facial soft tissue thickness norms in an adult Mediterranean population

The use of facial soft tissue thickness (FSTT) values is essential in forensic facial approximation. Few studies have assessed the FSTT norms in Mediterranean populations and none in the Lebanese population. The purpose of this study was to (1) present midsagittal facial FSTT norms for Lebanese adults with well-balanced faces and normal occlusion; (2) evaluate the presence of sexual dimorphism within these measurements; (3) establish a potential correlation between these measurements and (4) build on the existing database of FSTT data from previously published studies. FSTT measurements at 10 midsagittal locations were obtained from the lateral cephalometric radiographs of 87 males and 135 females (mean age of 23.49±6.24years). In additional to means, Shorth and 75-Shormax values are presented. Differences between sexes were assessed using the MANOVA test and correlations between different measurements were computed. The thinnest (3.07±0.72mm) and thickest (15.61±2.38mm) craniofacial soft tissue measurements existed at Rhinion and Subnasale, respectively. There was a statistically significant and large effect of sex on the combined FSTT variables (p<0.001; eta-squared=0.393). Males displayed larger FSTT values at all landmarks except at Glabella (p=0.162). Significant correlations were observed between almost all measurements with the highest being between the upper and lower lips (r=0.763) and between Pogonion and Gnathion (r=0.784). The descriptive values of FSTT values reported in this study add to the body of research necessary for the enhancement of facial approximation methods The uniquely strong effects of sex on FSTT measurements combined and on selected single FSTT measurements are an area for further research.

An overview of the latest developments in facial imaging

Facial imaging is a term used to describe methods that use facial images to assist or facilitate human identification. This pertains to two craniofacial identification procedures that use skulls and faces-facial approximation and photographic superimposition-as well as face-only methods for age progression/regression, the construction of facial graphics from eyewitness memory (including composites and artistic sketches), facial depiction, face mapping and newly emerging methods of molecular photofitting. Given the breadth of these facial imaging techniques, it is not surprising that a broad array of subject-matter experts participate in and/or contribute to the formulation and implementation of these methods (including forensic odontologists, forensic artists, police officers, electrical engineers, anatomists, geneticists, medical image specialists, psychologists, computer graphic programmers and software developers). As they are concerned with the physical characteristics of humans, each of these facial imaging areas also falls in the domain of physical anthropology, although not all of them have been traditionally regarded as such. This too offers useful opportunities to adapt established methods in one domain to others more traditionally held to be disciplines within physical anthropology (e.g. facial approximation, craniofacial superimposition and face photo-comparison). It is important to note that most facial imaging methods are not currently used for identification but serve to assist authorities in narrowing or directing investigations such that other, more potent, methods of identification can be used (e.g. DNA). Few, if any, facial imaging approaches can be considered honed end-stage scientific methods, with major opportunities for physical anthropologists to make meaningful contributions. Some facial imaging methods have considerably stronger scientific underpinnings than others (e.g. facial approximation versus face mapping), some currently lie entirely within the artistic sphere (facial depiction), and yet others are so aspirational that realistic capacity to obtain their aims has strongly been questioned despite highly advanced technical approaches (molecular photofitting). All this makes for a broad-ranging, dynamic and energetic field that is in a constant state of flux. This manuscript provides a theoretical snapshot of the purposes of these methods, the state of science as it pertains to them, and their latest research developments.

How tight is the relationship between the skeletal and soft-tissue facial profile: A geometric morphometric analysis of the facial outline

Correlations between facial bony structures and soft facial features are fundamental for facial approximation methods The purpose of this study was to assess the strength of the association between craniofacial shape and the shape of the soft-tissue profile and to determine the extent to which it might be possible to predict the latter from the former. Soft-tissue and skeletal facial profile curves were extracted from 86 lateral head cephalograms of a recent Central European population (52 males and 34 females, aged between 19 and 43 years), divided into five parts, segmented automatically and evaluated using geometric morphometrics. The magnitude of the hard-soft shape association was assessed by principal component analysis and subsequent multiple linear regression (Halazonetis, 2007), by partial least square analysis (PLS) (Rohlf and Corti, 2000) and the RV coefficient (Klingenberg, 2009). The greatest amount of association between the skeletal contour and overlying soft tissues was exhibited by the region of the forehead (predictive power: 95.1%, RV=0.91, correlation for PLS1 r=0,96), followed by the region of the nasal root (predictive power: 40.2%, RV=0.42, r_PLS1=0.72) and the lower lip and chin (predictive power: 37.3%, RV=0.41, r_PLS1=0.65). The smallest statistically significant covariation was displayed by the upper lip and the maxilla (predictive power: 9.6%, RV=0.14, r_PLS1=0.43). The shape covariation between the nasal bridge and the tip and lateral border of the nasal aperture was found to be statistically insignificant (predictive power: 5.8%, RV=0.05, r_PLS1=0.26). Shape covariation was visualized and described by thin-plate spine grids. These findings correspond with the observation that the shape of the nasal profile and the upper lip contour are difficult to reconstruct or predict reliably in facial approximations. It seems that the shape of soft tissues might not follow underlying structures as closely as expected.

A facial reconstruction method based on new mesh deformation techniques

This article presents a new numerical method for facial reconstruction. The problem is the following: given a dry skull, reconstruct a virtual face that would help in the identification of the subject. The approach combines classical features as the use of a skulls/faces database and more original aspects: (1) an original shape matching method is used to link the unknown skull to the database templates; (2) the final face is seen as an elastic 3D mask that is deformed and adapted onto the unknown skull. In this method, the skull is considered as a whole surface and not restricted to some anatomical landmarks, allowing a dense description of the skull/face relationship. Also, the approach is fully automated. Various results are presented to show its efficiency.

Assessment of accuracy and recognition of three-dimensional computerized forensic craniofacial reconstruction

Facial reconstruction is a technique that aims to reproduce the individual facial characteristics based on interpretation of the skull, with the objective of recognition leading to identification. The aim of this paper was to evaluate the accuracy and recognition level of three-dimensional (3D) computerized forensic craniofacial reconstruction (CCFR) performed in a blind test on open-source software using computed tomography (CT) data from live subjects. Four CCFRs were produced by one of the researchers, who was provided with information concerning the age, sex, and ethnic group of each subject. The CCFRs were produced using Blender® with 3D models obtained from the CT data and templates from the MakeHuman® program. The evaluation of accuracy was carried out in CloudCompare, by geometric comparison of the CCFR to the subject 3D face model (obtained from the CT data). A recognition level was performed using the Picasa® recognition tool with a frontal standardized photography, images of the subject CT face model and the CCFR. Soft-tissue depth and nose, ears and mouth were based on published data, observing Brazilian facial parameters. The results were presented from all the points that form the CCFR model, with an average for each comparison between 63% and 74% with a distance -2.5 ≤ x ≤ 2.5 mm from the skin surface. The average distances were 1.66 to 0.33 mm and greater distances were observed around the eyes, cheeks, mental and zygomatic regions. Two of the four CCFRs were correctly matched by the Picasa® tool. Free software programs are capable of producing 3D CCFRs with plausible levels of accuracy and recognition and therefore indicate their value for use in forensic applications.

A PCA-Based method for determining craniofacial relationship and sexual dimorphism of facial shapes

Previous studies have used principal component analysis (PCA) to investigate the craniofacial relationship, as well as sex determination using facial factors. However, few studies have investigated the extent to which the choice of principal components (PCs) affects the analysis of craniofacial relationship and sexual dimorphism. In this paper, we propose a PCA-based method for visual and quantitative analysis, using 140 samples of 3D heads (70 male and 70 female), produced from computed tomography (CT) images. There are two parts to the method. First, skull and facial landmarks are manually marked to guide the model's registration so that dense corresponding vertices occupy the same relative position in every sample. Statistical shape spaces of the skull and face in dense corresponding vertices are constructed using PCA. Variations in these vertices, captured in every principal component (PC), are visualized to observe shape variability. The correlations of skull- and face-based PC scores are analysed, and linear regression is used to fit the craniofacial relationship. We compute the PC coefficients of a face based on this craniofacial relationship and the PC scores of a skull, and apply the coefficients to estimate a 3D face for the skull. To evaluate the accuracy of the computed craniofacial relationship, the mean and standard deviation of every vertex between the two models are computed, where these models are reconstructed using real PC scores and coefficients. Second, each PC in facial space is analysed for sex determination, for which support vector machines (SVMs) are used. We examined the correlation between PCs and sex, and explored the extent to which the choice of PCs affects the expression of sexual dimorphism. Our results suggest that skull- and face-based PCs can be used to describe the craniofacial relationship and that the accuracy of the method can be improved by using an increased number of face-based PCs. The results show that the accuracy of the sex classification is related to the choice of PCs. The highest sex classification rate is 91.43% using our method.

Comparison Among Manual Facial Approximations Conducted by Two Methodological Approaches of Face Prediction

This study verified the difference between two methods of forensic facial approximation (FFA) regarding recognition and resemblance rates. Three-dimensional models of skulls were obtained from computerized tomography (CT) scans of two subjects (targets). Two manual FFAs were performed for each target, by applying two different guidelines for the facial structures (what we called "American method" (AM) and "Combined method" (CM)). Unfamiliar assessors evaluated the sculptures by recognition and resemblance tests. The AM was that which allowed more correct responses of recognition and higher resemblance's scores for the male target (p < 0.001). Regarding guidelines for modeling characteristics of the face, the ones that are practical and easily performed for sculptures, such as the length of the anterior nasal spine multiplied by 3 for nose prediction, may offer better results in terms of resemblance.

Densely calculated facial soft tissue thickness for craniofacial reconstruction in Chinese adults

Craniofacial reconstruction (CFR) is used to recreate a likeness of original facial appearance for an unidentified skull; this technique has been applied in both forensics and archeology. Many CFR techniques rely on the average facial soft tissue thickness (FSTT) of anatomical landmarks, related to ethnicity, age, sex, body mass index (BMI), etc. Previous studies typically employed FSTT at sparsely distributed anatomical landmarks, where different landmark definitions may affect the contrasting results. In the present study, a total of 90,198 one-to-one correspondence skull vertices are established on 171 head CT-scans and the FSTT of each corresponding vertex is calculated (hereafter referred to as densely calculated FSTT) for statistical analysis and CFR. Basic descriptive statistics (i.e., mean and standard deviation) for densely calculated FSTT are reported separately according to sex and age. Results show that 76.12% of overall vertices indicate that the FSTT is greater in males than females, with the exception of vertices around the zygoma, zygomatic arch and mid-lateral orbit. These sex-related significant differences are found at 55.12% of all vertices and the statistically age-related significant differences are depicted between the three age groups at a majority of all vertices (73.31% for males and 63.43% for females). Five non-overlapping categories are given and the descriptive statistics (i.e., mean, standard deviation, local standard deviation and percentage) are reported. Multiple appearances are produced using the densely calculated FSTT of various age and sex groups, and a quantitative assessment is provided to examine how relevant the choice of FSTT is to increasing the accuracy of CFR. In conclusion, this study provides a new perspective in understanding the distribution of FSTT and the construction of a new densely calculated FSTT database for craniofacial reconstruction.

Quantitative assessment of the facial features of a Mexican population dataset

The present study describes the morphological variation of a large database of facial photographs. The database comprises frontal (386 female, 764 males) and lateral (312 females, 666 males) images of Mexican individuals aged 14-69 years that were obtained under controlled conditions. We used geometric morphometric methods and multivariate statistics to describe the phenotypic variation within the dataset as well as the variation regarding sex and age groups. In addition, we explored the correlation between facial traits in both views. We found a spectrum of variation that encompasses broad and narrow faces. In frontal view, the latter is associated to a longer nose, a thinner upper lip, a shorter lower face and to a longer upper face, than individuals with broader faces. In lateral view, antero-posteriorly shortened faces are associated to a longer profile and to a shortened helix, than individuals with longer faces. Sexual dimorphism is found in all age groups except for individuals above 39 years old in lateral view. Likewise, age-related changes are significant for both sexes, except for females above 29 years old in both views. Finally, we observed that the pattern of covariation between views differs in males and females mainly in the thickness of the upper lip and the angle of the facial profile and the auricle. The results of this study could contribute to the forensic practices as a complement for the construction of biological profiles, for example, to improve facial reconstruction procedures.

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.

Giovanni Battista Morgagni: facial reconstruction by virtual anthropology

Multidisciplinary research was carried out on human skeletal remains to identify if they belonged to the famous pathologist Giovanni Battista Morgagni, who died at a very old age and was buried in a church in Padua. The purpose of this study was to analyze the skull, creating a virtual model necessary for facial reconstruction, so as to contribute to the identification of the skull. The skeletal remains were found buried in the Morgagni family grave. Based on preliminary anthropological evidence, that the skull might be ascribable to Giovanni Battista Morgagni, a digitized model of the skull was created and restored. From this, a virtual facial reconstruction was developed using an assumed relationship between the soft-tissues and the underlying skeletal structure. Finally, the anthropological profile and the face reconstruction were compared with historical documentation and the portrait of Morgagni by Pietro Danieletti, showing clear similarities. Virtual anthropological techniques create new perspectives for anthropological and medical studies and can be used successfully in the forensic sciences to make a positive identification, such as in this case, which has been examined by different experts with similar results.

Toward DNA-based facial composites: preliminary results and validation

The potential of constructing useful DNA-based facial composites is forensically of great interest. Given the significant identity information coded in the human face these predictions could help investigations out of an impasse. Although, there is substantial evidence that much of the total variation in facial features is genetically mediated, the discovery of which genes and gene variants underlie normal facial variation has been hampered primarily by the multipartite nature of facial variation. Traditionally, such physical complexity is simplified by simple scalar measurements defined a priori, such as nose or mouth width or alternatively using dimensionality reduction techniques such as principal component analysis where each principal coordinate is then treated as a scalar trait. However, as shown in previous and related work, a more impartial and systematic approach to modeling facial morphology is available and can facilitate both the gene discovery steps, as we recently showed, and DNA-based facial composite construction, as we show here. We first use genomic ancestry and sex to create a base-face, which is simply an average sex and ancestry matched face. Subsequently, the effects of 24 individual SNPs that have been shown to have significant effects on facial variation are overlaid on the base-face forming the predicted-face in a process akin to a photomontage or image blending. We next evaluate the accuracy of predicted faces using cross-validation. Physical accuracy of the facial predictions either locally in particular parts of the face or in terms of overall similarity is mainly determined by sex and genomic ancestry. The SNP-effects maintain the physical accuracy while significantly increasing the distinctiveness of the facial predictions, which would be expected to reduce false positives in perceptual identification tasks. To the best of our knowledge this is the first effort at generating facial composites from DNA and the results are preliminary but certainly promising, especially considering the limited amount of genetic information about the face contained in these 24 SNPs. This approach can incorporate additional SNPs as these are discovered and their effects documented. In this context we discuss three main avenues of research: expanding our knowledge of the genetic architecture of facial morphology, improving the predictive modeling of facial morphology by exploring and incorporating alternative prediction models, and increasing the value of the results through the weighted encoding of physical measurements in terms of human perception of faces.

Craniofacial reconstruction evaluation by geodesic network

Craniofacial reconstruction is to estimate an individual's face model from its skull. It has a widespread application in forensic medicine, archeology, medical cosmetic surgery, and so forth. However, little attention is paid to the evaluation of craniofacial reconstruction. This paper proposes an objective method to evaluate globally and locally the reconstructed craniofacial faces based on the geodesic network. Firstly, the geodesic networks of the reconstructed craniofacial face and the original face are built, respectively, by geodesics and isogeodesics, whose intersections are network vertices. Then, the absolute value of the correlation coefficient of the features of all corresponding geodesic network vertices between two models is taken as the holistic similarity, where the weighted average of the shape index values in a neighborhood is defined as the feature of each network vertex. Moreover, the geodesic network vertices of each model are divided into six subareas, that is, forehead, eyes, nose, mouth, cheeks, and chin, and the local similarity is measured for each subarea. Experiments using 100 pairs of reconstructed craniofacial faces and their corresponding original faces show that the evaluation by our method is roughly consistent with the subjective evaluation derived from thirty-five persons in five groups.

Anthropological facial approximation in three dimensions (AFA3D): computer-assisted estimation of the facial morphology using geometric morphometrics

This study presents Anthropological Facial Approximation in Three Dimensions (AFA3D), a new computerized method for estimating face shape based on computed tomography (CT) scans of 500 French individuals. Facial soft tissue depths are estimated based on age, sex, corpulence, and craniometrics, and projected using reference planes to obtain the global facial appearance. Position and shape of the eyes, nose, mouth, and ears are inferred from cranial landmarks through geometric morphometrics. The 100 estimated cutaneous landmarks are then used to warp a generic face to the target facial approximation. A validation by re-sampling on a subsample demonstrated an average accuracy of c. 4 mm for the overall face. The resulting approximation is an objective probable facial shape, but is also synthetic (i.e., without texture), and therefore needs to be enhanced artistically prior to its use in forensic cases. AFA3D, integrated in the TIVMI software, is available freely for further testing.