3D statistical shape analysis of the face in Apert syndrome

Timely diagnosis of craniofacial syndromes as well as adequate timing and choice of surgical technique are essential for proper care management. Statistical shape models and machine learning approaches are playing an increasing role in Medicine and have proven its usefulness. Frameworks that automate processes have become more popular. The use of 2D photographs for automated syndromic identification has shown its potential with the Face2Gene application. Yet, using 3D shape information without texture has not been studied in such depth. Moreover, the use of these models to understand shape change during growth and its applicability for surgical outcome measurements have not been analysed at length. This thesis presents a framework using state-of-the-art machine learning and computer vision algorithms to explore possibilities for automated syndrome identification based on shape information only. The purpose of this was to enhance understanding of the natural development of the Apert syndromic face and its abnormality as compared to a normative group. An additional method was used to objectify changes as result of facial bipartition distraction, a common surgical correction technique, providing information on the successfulness and on inadequacies in terms of facial normalisation. Growth curves were constructed to further quantify facial abnormalities in Apert syndrome over time along with 3D shape models for intuitive visualisation of the shape variations. Post-operative models were built and compared with age-matched normative data to understand where normalisation is coming short. The findings in this thesis provide markers for future translational research and may accelerate the adoption of the next generation diagnostics and surgical planning tools to further supplement the clinical decision-making process and ultimately to improve patients’ quality of life

Exploring How Faces Reveal Our Ethnicity

The human face varies with ethnicity as well as individually within any ethnotype. The ethnicvariation of the human face is seldom explicitly addressed in education. It would be of great value to foster the appreciation of the face as telling the story of the commonality of all of humankind and the diversity in our global distribution. Faces tell about origins and cultures. The language with which a face tells this story should be taught. It is a language not of words but of shapes, specifically three-dimensional shapes. Modern technology enables immersive visualization of three-dimensional shape in compelling ways that facilitate our learning a language with which to describe faces. An interactive animation framework is introduced that allows exploration of the space of ethnic variation via a set of intuitive, human understandable, facial shape properties. Parametric variation in these properties make explicit how our faces reveal our ethnicity

A finite element study of the human cranium : the impact of morphological variation on biting performance

This thesis investigated the relationship between craniofacial morphology and masticatory mechanics using finite element analysis (FEA). Chapter 1 is a literature review of the relevant background: bone mechanics, jaw-elevator muscle anatomy, imaging techniques, FEA and geometric morphometrics.The second, third and fourth chapters comprise experimental work aiming to provide a framework for FE model construction and loading. The second chapter aimed to validate the method for FE model building and assess the sensitivity of models to simplifications. Models with simplified bone anatomy and resolution predicted strains close to those measured experimentally. The third chapter assessed the predictability of muscle cross-sectional area (CSA) from bony features. It was found that muscle CSA, an estimator of muscle force, has low predictability. The fourth chapter assessed FE model sensitivity to variations in applied muscle forces. Results showed that a cranial FE model behaved reasonably robustly under variations in the muscle loading regimen.Chapter 5 uses the conclusions from the previous studies to build FE models of six human crania, including two individuals with artificial deformations of the neurocranium. Despite differences in form and the presence of deformation, all performed similarly during biting, varying mainly in the magnitudes of performance parameters. The main differences related to the form of the maxilla, irrespective of neurocranial deformation. The most orthognatic individuals with the narrowest maxilla showed the most distinctive deformation during incisor and molar bites, and achieved the greatest bite force efficiency. However, bite forces were similar among individuals irrespective of the presence of artificial deformation. This appears to relate to the preservation of normal dental occlusion, which in turn maintains similar loading and so morphogenesis of the mid face. Altogether, the results of this thesis show that FEA is reliable in comparing masticatory system functioning and point to how variations in morphology impact skeletal performance

Second Life: the seventh face of the library?

Viewpoint/Discussion Paper Purpose This paper gives a brief introduction to Second Life, an outline of how one academic librarian has got involved with using it and reviews the issues that have arisen from a library perspective. Approach It offers a reflection on whether library activities in Second Life are different to library services in the real world and suggests that Second Life is just another ‘face’ of the library. Findings Second Life is still in the very early stages of development. There are various barriers and challenges to overcome before it can be used widely within universities. However, this paper shows it does provide an opportunity to experiment and explore what information resources are required in this environment and how librarianship and librarians need to evolve to cater for users in a three dimensional world. Originality/value This paper is based on personal experience and offers as many questions as answers

Three-dimensional morphanalysis of the face.

The aim of the work reported in this thesis was to determine the extent to which orthogonal two-dimensional morphanalytic (universally relatable) craniofacial imaging methods can be extended into the realm of computer-based three-dimensional imaging. New methods are presented for capturing universally relatable laser-video surface data, for inter-relating facial surface scans and for constructing probabilistic facial averages. Universally relatable surface scans are captured using the fixed relations principle com- bined with a new laser-video scanner calibration method. Inter- subject comparison of facial surface scans is achieved using inter- active feature labelling and warping methods. These methods have been extended to groups of subjects to allow the construction of three-dimensional probabilistic facial averages. The potential of universally relatable facial surface data for applications such as growth studies and patient assessment is demonstrated. In addition, new methods for scattered data interpolation, for controlling overlap in image warping and a fast, high-resolution method for simulating craniofacial surgery are described. The results demonstrate that it is not only possible to extend universally relatable imaging into three dimensions, but that the extension also enhances the established methods, providing a wide range of new applications

Methodological Challenges in Eye-Tracking based Usability Testing of 3-Dimensional Software – Presented via Experiences of Usability Tests of Four 3D Applications

Eye-tracking based usability testing and User Experience (UX) research are widespread in the development processes of various types of software; however, there exist specific difficulties during usability tests of three-dimensional (3D) software. Analysing the screen records with gaze plots, heatmaps of fixations, and statistics of Areas of Interests (AOI), methodological problems occur when the participant wants to rotate, zoom, or move the 3D space. The data gained regarded the menu bar is mainly interpretable; however, the data regarded the 3D environment is hardly so, or not at all. Our research tested four software applications with the aforementioned problem in mind: ViveLab and Jack Digital Human Modelling (DHM) and ArchiCAD and CATIA Computer Aided Design (CAD) software. Our original goal was twofold. Firstly, with these usability tests, we aimed to identify issues in the software. Secondly, we tested the utility of a new methodology which was included in the tests. This paper summarizes the results on the methodology based on individual experiments with different software applications. One of the main ideas behind the methodology adopted is to tell the participants (during certain subtasks of the tests) not to move the 3D space while they perform the given tasks at a certain point in the usability test. During the experiments, we applied a Tobii eye-tracking device, and after the task completion, each participant was interviewed. Based on these experiences, the methodology appears to be both useful and applicable, and its visualisation techniques for one or more participants are interpretable

Kernel Truncated Regression Representation for Robust Subspace Clustering

Subspace clustering aims to group data points into multiple clusters of which each corresponds to one subspace. Most existing subspace clustering approaches assume that input data lie on linear subspaces. In practice, however, this assumption usually does not hold. To achieve nonlinear subspace clustering, we propose a novel method, called kernel truncated regression representation. Our method consists of the following four steps: 1) projecting the input data into a hidden space, where each data point can be linearly represented by other data points; 2) calculating the linear representation coefficients of the data representations in the hidden space; 3) truncating the trivial coefficients to achieve robustness and block-diagonality; and 4) executing the graph cutting operation on the coefficient matrix by solving a graph Laplacian problem. Our method has the advantages of a closed-form solution and the capacity of clustering data points that lie on nonlinear subspaces. The first advantage makes our method efficient in handling large-scale datasets, and the second one enables the proposed method to conquer the nonlinear subspace clustering challenge. Extensive experiments on six benchmarks demonstrate the effectiveness and the efficiency of the proposed method in comparison with current state-of-the-art approaches.Comment: 14 page