Facial Reconstruction as a Regression Problem

This chapter presents a computer-assisted method for facial reconstruction. This method provides an estimation of the facial outlook associated with unidentified skeletal remains. Current computer-assisted methods using a statistical framework rely on a common set of points extracted form the bone and soft-tissue surfaces. Facial reconstruction then attempts to predict the position of the soft-tissue surface points knowing the positions of the bone surface points. This chapter proposes to use linear latent variable regression methods for the prediction (such as Principal Component Regression or Latent Root Root Regression) and to compare the results obtained to those given by the use of statistical shape models. In conjunction, the influence of the number of skull landmarks used was evaluated. Anatomical skull landmarks are completed iteratively by points located upon geodesics linking the anatomical landmarks. They enable artificial augmentation of the number of skull points. Facial landmarks are obtained using a mesh-matching algorithm between a common reference mesh and the individual soft-tissue surface meshes. The proposed method is validated in terms of accuracy, based on a leave-one-out cross-validation test applied on a homogeneous database. Accuracy measures are obtained by computing the distance between the reconstruction and the ground truth. Finally, these results are discussed in regard to current computer-assisted facial reconstruction techniques, including deformation based techniques.

Automating Human Identification Using Dental X-Ray Radiographs

The goal of forensic dentistry is to identify individuals based on their dental characteristics. This chapter presents a system for automating that process by identifying people from dental X-ray images. Given a dental image of a postmortem (PM), the proposed system retrieves the best matches from an antemortem (AM) database. The system automatically segments dental X-ray images into individual teeth and extracts representative feature vectors for each tooth, which are later used for retrieval. This chapter details a new method for teeth segmentation, and three different methods for representing and matching teeth. Each method has a different technique for representing the tooth shape and has its advantages and disadvantages compared with the other methods. The first method represents each tooth contour by signature vectors obtained at salient points on the contour of the tooth. The second method uses Hierarchical Chamfer distance for matching AM and PM teeth. In the third method, each tooth is described using a feature vector extracted using the force field energy function and Fourier descriptors. During retrieval, according to a matching distance between the AM and PM teeth, AM radiographs that are most similar to a given PM image, are found and presented to the user. To increase the accuracy of the identification process, the three matching techniques are fused together. The fusion of information is an integral part of any identification system to improve the overall performance. This chapter introduces some scenarios for fusing the three matchers at the score level as well as at the fusion level.

Resolving Sample Traces in Complex Mixtures with Microarray Analyses

This chapter reviews the microarray technology and deal with the majority of aspects regarding microarrays. It focuses on today’s knowledge of separation techniques and methodologies of complex signal, i.e. samples. Overall, the chapter reviews the current knowledge on the topic of microarrays and presents the analyses and techniques used, which facilitate such approaches. It starts with the theoretical framework on microarray technology; second, the chapter gives a brief review on statistical methods used for microarray analyses, and finally, it contains a detailed review of the methods used for discriminating traces of nucleic acids within a complex mixture of samples.

Forensic Statistics in Health Sciences

This chapter reviews the application of forensic statistical methods related issues such as: methods of deciphering evidence, DNA profile matching, searching a database of DNA profiles, scientific reliability, discrimination in presentation of statistical evidence in legal settings, assumptions in underlying statistical analysis when evidence is presented, precision & accuracy, role of using extreme values in evidence, and decision analysis in forensic science. The emphasis of the chapter is on concepts from statistical application, nature, and use of evidences in everyday clinical practice and in the court of law. Another goal of the chapter is to serve as a central reference to access of information about resources related to this topic.

Left-Right Asymmetries and other Common Anatomical Variants of Temporomandibular Articular Surfaces

In this chapter, the authors describe systematically left-right asymmetries and other common anatomical variants of the temporomandibular articular surfaces as they can appear in daily clinical practice. Digital photography and macroscopic observation were used to evaluate morphologic features of TMJ surfaces of elderly subjects at 100 glenoid fossae and articular eminences of dried skull bases, and at 100 dried mandibles. Mandibular condyle shape in the horizontal plane and in the frontal plane were evaluated using a standardized classification devised by Öberg et al. (1971). Degenerative form and surface changes of the TMJ were assessed using a scale devised by Wedel et al. (1978). The antero-posterior and medio-lateral diameter of the temporomandibular articular surfaces were measured using a digital caliper. The orientation was determined using a clinical goniometer. Morphologic left-right asymmetries of the temporomandibular articular surfaces were frequently present in mandibular condyles and in glenoid fossae. In general, mandibular condyles showed more often morphologic left-right asymmetries than glenoid fossae. Anatomical variants of the articular surfaces of the left and right mandibular condyles resulted from differences in shape. The majority of the articular surfaces had an oblong horizontal outline and a rounded frontal outline. One fifth of the mandibular condyles showed pear-shaped horizontal outlines and flat or ridge-shaped frontal outlines. An important incidence of left-right asymmetries and other common anatomical variants of the temporomandibular articular joint surfaces must be considered at observation and therapy of the temporomandibular joint; arthrokinematic functional consequences may result.

Dental Age Assessment (DAA) of Children and Emerging Adults

A variety of methods have been used to estimate dental age. Tooth development as a means of estimating age has been used for several centuries. The purpose of the chapter is to describe the method used at the Dental Paediatric Unit of King’s College London Dental Institute and the UCL Eastman Dental Institute to carry out Dental Age Assessment (DAA). An important principle is the biological variability of growth of teeth, a factor inappropriately considered in many studies of DAA. This chapter serves to inform colleagues, lawyers, immigration workers, social workers and subjects of unknown date of birth of the way in which DAA is conducted.

Digital Applications in Forensic Odontology

Forensic Odontology or forensic dentistry is the use of dental expertise, dental findings, and dental facts in legal proceedings. The principal efforts of dentists in this regard are geared toward establishing the identity of unknown human remains or verifying the identity of visually unrecognizable human remains. The digital revolution has impacted all aspects of forensic odontology. This chapter will discuss the impact on person identification through dental means, dental identification in mass or disaster victim incidents, establishing the age of an unknown individual or human remains through dental examination, digital photography in dentistry and forensic odontology, and the use of digital methods in the analysis and comparison of bite mark evidence.

Predictive Dynamical Modelling MicroRNAs Role in Complex Networks

The aim of this chapter is to give an extended analytical consideration of mathematical modelling of the microRNA role in cancer networks. For this purpose, ordinary and partial differential equations are used for synthesizing and analyzing the models of gene, microRNAs and mRNAs concentration alterations as time-dependent variables related by functional and differential relations. The architecture of the models and the definitions of their components are inspired by the qualitative theory of differential equations. This chapter’s analysis shows that it is able to ensure the authenticity and validity of the following qualitative conclusions: (a) the rates of protein production decrease with the increasing constant production rate of microRNA at microRNA-mediated target regulation on mRNAs; (b) time delay has a stabilizing role in the interaction between the miRNA-17-92 cluster and the transcription factors E2F and Myc.

Data Hiding in Digitized Medical Images

This chapter envelops data hiding techniques applied to medical images for improving their security. It covers types of medical images, their security requirements and types of threats to them. This provides a sufficient background and reasoning for applying data hiding techniques to the medical images. The purpose of this chapter is to study requirements of data hiding techniques with respect to medical imaging and to cover state of art methods in this domain. These techniques are developed from different application perspectives helping to understand their limitations and strengths. The chapter culminates with study of algorithms for reversible watermarking techniques and discussion on future of watermarking in medical domain.

Laser Scanning Confocal Imaging of Forensic Samples and Their 3D Visualization

This chapter describes the application of confocal imaging in fluorescence and reflection modes and the analysis of the three-dimensional (3D) data sets of samples relevant to forensic medical investigations. In the last three decades, confocal microscopy has become a widely used technique in the fields of biological and medical sciences. Gradually, its use is becoming more widespread in forensic sciences as it offers numerous advantages over conventional wide-field microscopy. One of the key advantages is the generation of sharply focused 3D data stacks of imaged material, without out-of-focus blur. The technique generates digital optical sections from sample surface down to a depth of 100-300 µm from which a multitude of structural, sculptural and optical parameters in 3D and 4D can be obtained and analysed. This chapter discusses several examples of confocal imaging for medical forensic applications, including the 3D analysis of finger prints, hair, skin abrasions and grass pollen exine morphology to provide new diagnostic and prognostic information. The chapter also covers practical applications of a powerful 3D visualization and analyses software.