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

There are numerous anatomical and anthropometrical standards that can be utilised for craniofacial analysis and identification. These standards originate from a wide variety of sources, such as orthodontic, maxillofacial, surgical, anatomical, anthropological and forensic literature, and numerous media have been employed to collect data from living and deceased subjects. With the development of clinical imaging and the enhanced technology associated with this field, multiple methods of data collection have become accessible, including Computed Tomography, Cone-Beam Computed Tomography, Magnetic Resonance Imaging, Radiographs, Three-dimensional Scanning, Photogrammetry and Ultrasound, alongside the more traditional in vivo methods, such as palpation and direct measurement, and cadaveric human dissection.

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.

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

Background: The human mandible is variable in shape, size and position and any deviation from normal can affect the facial appearance and dental occlusion.

Objectives: The objectives of this study were to determine whether the Sassouni cephalometric analysis could help predict two-dimensional mandibular shape in humans using cephalometric planes and landmarks.

Materials And Methods: A retrospective computerised analysis of 100 lateral cephalometric radiographs taken at Kingston Hospital Orthodontic Department was carried out.

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

Predicting the possible age-related changes to a child's face, age progression methods modify the shape, colour and texture of a facial image while retaining the identity of the individual. However, the techniques vary between different practitioners. This study combines different age progression techniques for juvenile subjects, various researches based on longitudinal radiographic data; physical anthropometric measurements of the head and face; and digital image measurements in pixels.

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

Background: Prediction of the nose from the skull remains an important issue in forensic facial approximation. In 2010, Rynn et al. published a method of predicting nose projection from the skull.

Comparison of three-dimensional facial morphology between upright and supine positions employing three-dimensional scanner from live subjects.

Facial soft tissue thicknesses (FSTT) measurements collected from Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) imaging techniques are most commonly taken in the supine position for forensic craniofacial reconstruction. FSTT have been shown to be different in comparison to the upright position due to gravity. The variation of facial morphology between the upright and supine position of laser-scanned images taken from 44 individuals was investigated using volumetric analysis with deviation maps.

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.