[Modern opportunities of using computer programs and mobile devices in the frame of personality identification]. / Sovremennye vozmozhnosti ispol'zovaniya komp'yuternykh programm i mobil'nykh ustroistv v ramkakh identifikatsii lichnosti.

A technology of mobile devices on the basis of Android and iOS sharing, in which previously trained neural networks on the mobile device with the use of the Skull-face program place the reference points in automatic mode with subsequent analysis of the images and obtaining the result in less than 1 min, has been developed. Data processing and acquisition of results immediately at the scene of an accident can provide invaluable assistance in the mass admission of unidentified corpses in cases of emergency; will allow to rapidly, excluding the influence of subjective factor, solve expert tasks, improve the accuracy, effectiveness and performance of forensic personality identification.

Facial soft tissue depth of a contemporary adult Greek population.

Facial approximation is a technique that involves constructing the facial muscles and applying a suitable facial soft tissue depth (FSTD) dataset. To date, several FSTD studies have been conducted for varying population groups. This study aims to establish a FSTD dataset of an adult Greek population sample for the first time. The facial depths of subjects were measured on 100 head CT scans of 50 male and 50 female subjects aged from 18 to 99. The 3D head and skull models of subjects were segmented in Amira 6.1 by using histogram method. FSTDs were measured at 22 cranial landmarks (5 mid-sagittal, 17 bilateral). The FSTD dataset was generated by considering the age and sex of subjects. The impact of age and sex on the FSTD was limited. Slight inter-population depth variations were reported. Facial asymmetry calculated between the bilateral landmarks was insignificant for both male and female subjects.

Global facial soft tissue thicknesses for craniofacial identification (2023): a review of 140 years of data since Welcker's first study.

This year (2023) marks 140 years since the first publication of a facial soft tissue thickness (FSTT) study. Since 1883, a total of 139 studies have been published, collectively tallying > 220,000 tissue thickness measurements of > 19,500 adults. In just the last 5-years, 33 FSTT studies have been conducted. Herein, we add these data (plus an additional 20 studies) to the 2018 T-Table to provide an update of > 81,000 new datapoints to the global tallied facial soft tissue depths table. In contrast to the original 2008 T-Table, some notable changes are as follows: increased FSTTs by 3 mm at infra second molar (ecm2-iM2'), 2.5 mm at gonion (go-go'), 2 mm at mid-ramus (mr-mr'), and 1.5 mm at zygion (zy-zy'). Rolling grand means indicate that stable values have been attained for all nine median FSTT landmarks, while six out of nine bilateral landmarks continue to show ongoing fluctuations, indicating further data collection at these landmarks holds value. When used as point estimators for individuals with known values across 24 landmarks (i.e., C-Table data), the updated grand means produce slightly less estimation error than the 2018 T-Table means (3.5 mm versus 3.6 mm, respectively). Future efforts to produce less noisy datasets (i.e., reduce measurement and sampling errors as much as possible between studies) would be useful.

Computer-aided craniofacial superimposition validation study: the identification of the leaders and participants of the Polish-Lithuanian January Uprising (1863-1864).

In 2017, a series of human remains corresponding to the executed leaders of the "January Uprising" of 1863-1864 were uncovered at the Upper Castle of Vilnius (Lithuania). During the archeological excavations, 14 inhumation pits with the human remains of 21 individuals were found at the site. The subsequent identification process was carried out, including the analysis and cross-comparison of post-mortem data obtained in situ and in the lab with ante-mortem data obtained from historical archives. In parallel, three anthropologists with diverse backgrounds in craniofacial identification and two students without previous experience attempted to identify 11 of these 21 individuals using the craniofacial superimposition technique. To do this, the five participants had access to 18 3D scanned skulls and 14 photographs of 11 different candidates. The participants faced a cross-comparison problem involving 252 skull-face overlay scenarios. The methodology follows the main agreements of the European project MEPROCS and uses the software Skeleton-ID™. Based on MEPROCS standard, a final decision was provided within a scale, assigning a value in terms of strong, moderate, or limited support to the claim that the skull and the facial image belonged (or not) to the same person for each case. The problem of binary classification, positive/negative, with an identification rate for each participant was revealed. The results obtained in this study make the authors think that both the quality of the materials used and the previous experience of the analyst play a fundamental role when reaching conclusions using the CFS technique.

Cranial and facial inter-landmark distances and tissue depth dataset from computed tomography scans of 388 living persons.

Computed tomography (CT) scans of 388 living adults of both sexes were collected from four self-identified ancestry groups from the United States (African, Asian, European, and Hispanic). Scans were acquired from multiple institutions and under a variety of scanning protocols. Scans were used to produce 3D bone and soft tissue models, from which were derived cranial and facial inter-landmark distances (ILDs) and soft tissue depth measurements. Similar measurements were made on 3D facial approximations produced by ReFace software. 3D models and all measurements were obtained using MimicsR software. These measurements are useful for facial approximations of unidentified decedents and for investigations into human variation between and among ancestry groups and sexes.

Using Computed Tomography (CT) Data to Build 3D Resources for Forensic Craniofacial Identification.

Forensic craniofacial identification encompasses the practices of forensic facial approximation (aka facial reconstruction) and craniofacial superimposition within the field of forensic art in the United States. Training in forensic facial approximation methods historically has used plaster copies, high-cost commercially molded skulls, and photographs. Despite the increased accessibility of computed tomography (CT) and the numerous studies utilizing CT data to better inform facial approximation methods, 3D CT data have not yet been widely used to produce interactive resources or reference catalogs aimed at forensic art practitioner use or method standardization. There are many free, open-source 3D software packages that allow engagement in immersive studies of the relationships between the craniofacial skeleton and facial features and facilitate collaboration between researchers and practitioners. 3D CT software, in particular, allows the bone and soft tissue to be visualized simultaneously with tools such as transparency, clipping, and volume rendering of underlying tissues, allowing for more accurate analyses of bone to soft tissue relationships. Analyses and visualization of 3D CT data can not only facilitate basic research into facial variation and anatomical relationships relevant for reconstructions but can also lead to improved facial reconstruction guidelines. Further, skull and face surface models exported in digital 3D formats allow for 3D printing of custom reference models and novel training materials and modalities for practitioners. This chapter outlines the 3D resources that can be built from CT data for forensic craniofacial identification methods, including how to view 3D craniofacial CT data and modify surface models for 3D printing.

Testing regression and mean model approaches to facial soft-tissue thickness estimation.

Average facial soft-tissue thickness (FSTT) databanks are continuously developed and applied within craniofacial identification. This study considered and tested a subject-specific regression model alternative for estimating the FSTT values for oral midline landmarks using skeletal projection measurements. Measurements were taken from cone-beam computed tomography scans of 100 South African individuals (60 male, 40 female; Mage = 35 years). Regression equations incorporating sex categories were generated. This significantly improved the goodness-of-fit (r2-value). Validation tests compared the constructed regression models with mean FSTT data collected from this study, existing South African FSTT data, a universal total weighted mean approach with pooled demographic data and collection techniques and a regression model approach that uses bizygomatic width and maximum cranial breadth dimensions. The generated regression equations demonstrated individualised results, presenting a total mean inaccuracy (TMI) of 1.53 mm using dental projection measurements and 1.55 mm using cemento-enamel junction projection measurements. These slightly outperformed most tested mean models (TMI ranged from 1.42 to 4.43 mm), and substantially outperformed the pre-existing regression model approach (TMI = 5.12 mm). The newly devised regressions offer a subject-specific solution to FSTT estimation within a South African population. A continued development in sample size and validation testing may help substantiate its application within craniofacial identification.

Mouth Width and Cupid's Bow Estimation in a Southern African Population.

Standards for estimating mouth width and Cupid's bow width in craniofacial approximation and superimposition are limited. Currently, the only guideline for mouth width, using direct skeletal references, is a general rule indicating a 75% inter-canine to mouth width ratio. The philtrum, which closely corresponds to the Cupid's bow, is said to be equal to the inter-superior prominences of the maxillary central incisors. This study tested these guidelines against newly generated regression models and mean values. Cone-beam CT scans of 120 black and 39 white southern African adults were used. Comparative hard and soft tissue measurements were taken using a 3D DICOM viewer. Regression equations accounting population, sex, and approximate age variables (20-39 and 40+ years), utilizing maxillary inter-canine width to estimate mouth width and maxillary central-lateral incisor junction width to estimate Cupid's bow width, performed statistically best. The regression models were more reliable than existing standards in validation tests.

B-mode Ultrasound Measurement of Facial Soft Tissue Thickness for Craniofacial Identification: A Standardized Approach.

Facial soft tissue thicknesses (FSTT) have long formed a quantitative cornerstone of craniofacial identification methods. Measurement approaches could, however, be improved by standardization that enhances the utility/comparability of these FSTT data between studies and authors. This applies equally within the broad classes of measurement techniques, just as it does between them, where many different varieties of tools, tool settings, and practitioner techniques are used within each measurement modality. Although B-mode ultrasound is popularly used and holds some prime advantages, such as the measurement of upright living subjects, technical recommendations that provide basic underlying data structure and standardization are essentially nonexistent. This paper provides the first systematic and illustrated description of a standardized B-mode ultrasound measurement method designed to maximize data utility for craniofacial identification 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 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.

Open-Source Tools for Dense Facial Tissue Depth Mapping of Computed Tomography Models.

Computed tomography (CT) scans provide anthropologists with a resource to generate three-dimensional (3D) digital skeletal material to expand quantification methods and build more standardized reference collections. The ability to visualize and manipulate the bone and skin of the face simultaneously in a 3D digital environment introduces a new way for forensic facial approximation practitioners to access and study the face. Craniofacial relationships can be quantified with landmarks or with surface-processing software that can quantify the geometric properties of the entire 3D facial surface. This article describes tools for the generation of dense facial tissue depth maps (FTDMs) using deidentified head CT scans of modern Americans from the Cancer Imaging Archive public repository and the open-source program Meshlab. CT scans of 43 females and 63 males from the archive were segmented and converted to 3D skull and face models using Mimics and exported as stereolithography files. All subsequent processing steps were performed in Meshlab. Heads were transformed to a common orientation and coordinate system using the coordinates of nasion, left orbitale, and left and right porion. Dense FTDMs were generated on hollowed, cropped face shells using the Hausdorff sampling filter. Two new point clouds consisting of the 3D coordinates for both skull and face were colorized on an RGB (red-green-blue) scale from 0.0 (red) to 40.0-mm (blue) depth values and exported as polygon (PLY) file format models with tissue depth values saved in the "vertex quality" field. FTDMs were also split into 1.0-mm increments to facilitate viewing of common depths across all faces. In total, 112 FTDMs were generated for 106 individuals. Minimum depth values ranged from 1.2 mm to 3.4 mm, indicating a common range of starting depths for most faces regardless of weight, as well as common locations for these values over the nasal bones, lateral orbital margins, and forehead superior to the supraorbital border. Maximum depths were found in the buccal region and neck, excluding the nose. Individuals with multiple scans at visibly different weights presented the greatest differences within larger depth areas such as the cheeks and neck, with little to no difference in the thinnest areas. A few individuals with minimum tissue depths at the lateral orbital margins and thicker tissues over the nasal bones (>3.0 mm) suggested the potential influence of nasal bone morphology on tissue depths. This study produced visual quantitative representations of the face and skull for forensic facial approximation research and practice that can be further analyzed or interacted with using free software. The presented tools can be applied to preexisting CT scans, traditional or cone beam, adult or subadult individuals, with or without landmarks, and regardless of head orientation, for forensic applications as well as for studies of facial variation and facial growth. In contrast with other facial mapping studies, this method produced both skull and face points based on replicable geometric relationships, producing multiple data outputs that are easily readable with software that is openly accessible.

Re-assessment of South African juvenile facial soft tissue thickness data for craniofacial approximation: A comparative analysis using central tendency statistics.

Facial soft tissue thickness (FSTT) data form the basis of craniofacial identification methods such as facial approximation in cases where unknown skeletal remains lack unique identifiers such as fingerprints, DNA and dental records. Appropriate FSTT data are said to be required to produce accurate facial approximations that may be recognised by relatives. This view led to a vast number of studies considering subdivisions of FSTT data according to ancestry, age and sex. The paucity of South African juvenile FSTT standards of particular age groups, sex and ancestry is therefore problematic as "accurate" facial approximations cannot be produced. However, the use of pooled datasets and central tendency statistics offers a unique opportunity to circumvent the problem of small or absent FSTT datasets. The aim of this study was to use central tendency statistics of previously published South African data in order to assess whether it is necessary to subdivide FSTT datasets into different subgroups. In addition, a meta-analysis using central tendency statistics of 11 datasets within the C-table repository using the free open source TDStats programme (available through CRANIOFACIALidentification.com) for midfacial landmarks was performed. These datasets comprised of raw juvenile and adult FSTT data gathered from 1895 to 2015 as measured by a variety of methods Scatter plots showed that FSTT correlation with age is rather weak, while Kernel density plots of FSTT by sex and landmark indicated no difference between South African juvenile males and females. In order to test the practical application of FSTT data, two facial approximations were constructed - one based on the shorth from South African data and C-tables and one based on an American dataset. When comparing the two facial approximations based on different datasets, geometric deviation indicated differences at midline and bilateral landmarks, but the visual presentation of the facial approximations was similar. Therefore it is suggested that differences of less than 3mm at any landmark do not result in profound practical differences in the juvenile face. Subcategorizing juvenile data is not necessary as the same result can be achieved by weighted means as presented in the sub-adult C-tables.

TDStats-A fast standardized capability for facial soft tissue thickness analysis in R.

The popular and repeated calculation of facial soft tissue thickness in different samples by different practitioners makes the development of a free, standard, and open-source tool that calculates all necessary statistics in an automated fashion useful. This tool should enable data analysis for single or multiple studies in both independent study-specific format and as a pooled aggregate. The tool should be fast, should facilitate exploratory data analysis, and should provide robust central tendency statistics (shorth and shormaxes). The tool should facilitate effortless analysis, so that once the raw data are entered, little additional input is required of the analyst to maximize user-friendliness. This paper describes in detail such a capability (TDStats v2017.1) specifically formulated for soft tissue thickness analyses and demonstrates its utility by analysing 14,201 publically available data points at 24 landmarks from 1086 subjects in under 45s. Outputs include 120 plots, 15 tables, and 5 summary pdfs. A step-by-step user guide to TDStats is provided as well as additional comments and clarity on the utility of robust central tendency statistics.

2018 tallied facial soft tissue thicknesses for adults and sub-adults.

The tallied facial soft tissue thicknesses (or T-Tables) represent grand means of published facial soft tissue thickness sample means. These sample means have been drawn from across the full-breadth of the facial soft tissue thickness (FSTT) literature, including forensic science, anthropology and odontology. The report of new summary statistics for >1290 new sub-adults and >2200 new adults since the last T-Table calculation, in 2008 for sub-adults and 2013 for adults respectively, makes their update timely. The maximum sample sizes at any landmark now stand at 3023 for individuals aged 0-11 years old (g-g'); 3145 for individuals aged 12-17 years old (n-se'); and 10,333 for adults (n-se'). Following the recalculation of grand weighted means and comparison to the original 2008 data, some shifts in the T-Table statistics are evident at specific landmarks, namely: 2-2.5mm increases at gonion (go-go') and mid-mandibular border (mmb-mmb') for adults; 3.5mm decrease at gonion (go-go') for 12-17year olds; and 2.0mm decrease at menton (me-me') for 0-11year olds. Differences at all other landmarks (91-100% depending on the dataset) were minimal being <1.0mm. Performance tests of the new grand means as point estimators (using individuals with known FSTT size from the C-Table), show the 2018 T-Table statistics to produce marginally less error than the 2013 means: 2018 standard error of the estimate=3.7mm in contrast to 2013 standard error of the estimate=3.9mm. The long run nature of the T-Table statistics (i.e., big data) and quantified performance test accuracies on known subjects, earmark the 2018 T-Table as the premier FSTT standard for craniofacial identification casework. In the distant future, this is likely to change as the C-Table raw data repository grows, allowing shorths and shormaxes to be calculated for large samples. Given current raw data repository sample sizes of 0-1574 for T-Table landmarks (notably lower for younger individuals), there is some way to go before enhanced central tendency estimators can entirely replace untrimmed arithmetic means.

Estimating the Skull-to-Camera Distance from Facial Photographs for Craniofacial Superimposition.

The overlay of a skull and a face image for identification purposes requires similar subject-to-camera distances (SCD) to be used at both photographic sessions so that differences in perspective do not compromise the anatomical comparisons. As the facial photograph is the reference standard, it is crucial to determine its SCD first and apply this value to photography of the skull. So far, such a method for estimating the SCD has been elusive (some say impossible), compromising the technical validity of the superimposition procedure. This paper tests the feasibility of using the palpebral fissure length and a well-established photographic algorithm to accurately estimate the SCD from the facial photograph. Recordings at known SCD across a 1-10 m range (repeated under two test conditions) demonstrate that the newly formulated method works: a mean SCD estimation error of 7% that translates into <1% perspective distortion error between estimated and actual conditions.

Photo-Realistic Statistical Skull Morphotypes: New Exemplars for Ancestry and Sex Estimation in Forensic Anthropology.

Graphic exemplars of cranial sex and ancestry are essential to forensic anthropology for standardizing casework, training analysts, and communicating group trends. To date, graphic exemplars have comprised hand-drawn sketches, or photographs of individual specimens, which risks bias/subjectivity. Here, we performed quantitative analysis of photographic data to generate new photo-realistic and objective exemplars of skull form. Standardized anterior and left lateral photographs of skulls for each sex were analyzed in the computer graphics program Psychomorph for the following groups: South African Blacks, South African Whites, American Blacks, American Whites, and Japanese. The average cranial form was calculated for each photographic view, before the color information for every individual was warped to the average form and combined to produce statistical averages. These mathematically derived exemplars-and their statistical exaggerations or extremes-retain the high-resolution detail of the original photographic dataset, making them the ideal casework and training reference standards.

Study on the criteria for assessing skull-face correspondence in craniofacial superimposition.

Craniofacial superimposition has the potential to be used as an identification method when other traditional biological techniques are not applicable due to insufficient quality or absence of ante-mortem and post-mortem data. Despite having been used in many countries as a method of inclusion and exclusion for over a century it lacks standards. Thus, the purpose of this research is to provide forensic practitioners with standard criteria for analysing skull-face relationships. Thirty-seven experts from 16 different institutions participated in this study, which consisted of evaluating 65 criteria for assessing skull-face anatomical consistency on a sample of 24 different skull-face superimpositions. An unbiased statistical analysis established the most objective and discriminative criteria. Results did not show strong associations, however, important insights to address lack of standards were provided. In addition, a novel methodology for understanding and standardizing identification methods based on the observation of morphological patterns has been proposed.

MEPROCS framework for Craniofacial Superimposition: Validation study.

Craniofacial Superimposition (CFS) involves the process of overlaying a skull with a number of ante-mortem images of an individual and the analysis of their morphological correspondence. The lack of unified working protocols and the absence of commonly accepted standards, led to contradictory consensus regarding its reliability. One of the more important aims of 'New Methodologies and Protocols of Forensic Identification by Craniofacial Superimposition (MEPROCS)' project was to propose a common framework for CFS, what can be considered the first international standard in the field. The framework aimed to serve as a roadmap for avoiding particular assumptions that could bias the process. At the same time, it provides some empirical support to certain practices, technological means, and morphological criteria expected to facilitate the application of the CFS task and to improve its reliability. In order to confirm the utility and potential benefits of the framework use, there is a need to empirically evaluate it in CFS identification scenarios as close as possible to the reality. Thus, the purpose of this study is to validate the CFS framework developed. For that aim 12 participants were asked to report about a variable number of CFS following all the recommendations of the framework. The results are analysed and discussed according to the framework understanding and fulfilment, the participants' performance, and the correlation between expected decisions and those given by the participants. In view of the quantitative results and qualitative examination criteria we can conclude that those who follow the MEPROCS recommendations improve their performance.

Facial Soft Tissue Depth Measurement: Validation of the 75-Shormax.

The shorth and 75-shormax were recently posited as an improved alternative to the arithmetic mean for describing facial soft tissue thicknesses in craniofacial identification. The shorth better estimates the data peak, while the 75-shormax provides improved provisions for a long right tail. When first proposed, the 75-shormax was subjectively gauged. Herein, shormax errors are calculated at every whole percentile to quantitatively determine zones of error minimization in two large samples: (a) CT data of French adults, n-range = 211-469 individuals; and (b) all C-Table data, n-range = 60-1065 individuals [including part but not all of sample (a)]. The smallest residuals were found at the 79th percentile (mean of raw residuals) and the 74th percentile (mean of absolute residuals). The 75-shormax is subsequently verified as good error minimizer since the absolute differences carry the greatest weight and the 74th percentile closely approximates the 75th percentile.