Tim J. Hutton

3D analysis of facial morphology

Dense surface models can be used to analyze 3D facial morphology by establishing a correspondence of thousands of points across each 3D face image. The models provide dramatic visualizations of 3D face‐shape variation with potential for training physicians to recognize the key components of particular syndromes. We demonstrate their use to visualize and recognize shape differences in a collection of 3D face images that includes 280 controls (2 weeks to 56 years of age), 90 individuals with Noonan syndrome (NS) (7 months to 56 years), and 60 individuals with velo‐cardio‐facial syndrome (VCFS; 3 to 17 years of age). Ten‐fold cross‐validation testing of discrimination between the three groups was carried out on unseen test examples using five pattern recognition algorithms (nearest mean, C5.0 decision trees, neural networks, logistic regression, and support vector machines). For discriminating between individuals with NS and controls, the best average sensitivity and specificity levels were 92 and 93% for children, 83 and 94% for adults, and 88 and 94% for the children and adults combined. For individuals with VCFS and controls, the best results were 83 and 92%. In a comparison of individuals with NS and individuals with VCFS, a correct identification rate of 95% was achieved for both syndromes. This article contains supplementary material, which may be viewed at the American Journal of Medical Genetics website at http://www.interscience.wiley.com/jpages/0148‐7299/suppmat/index.html.

Estimating average growth trajectories in shape-space using kernel smoothing

In this paper, we show how a dense surface point distribution model of the human face can be computed and demonstrate the usefulness of the high-dimensional shape-space for expressing the shape changes associated with growth and aging. We show how average growth trajectories for the human face can be computed in the absence of longitudinal data by using kernel smoothing across a population. A training set of three-dimensional surface scans of 199 male and 201 female subjects of between 0 and 50 years of age is used to build the model.

Discriminating power of localized three-dimensional facial morphology

Many genetic syndromes involve a facial gestalt that suggests a preliminary diagnosis to an experienced clinical geneticist even before a clinical examination and genotyping are undertaken. Previously, using visualization and pattern recognition, we showed that dense surface models (DSMs) of full face shape characterize facial dysmorphology in Noonan and in 22q11 deletion syndromes. In this much larger study of 696 individuals, we extend the use of DSMs of the full face to establish accurate discrimination between controls and individuals with Williams, Smith-Magenis, 22q11 deletion, or Noonan syndromes and between individuals with different syndromes in these groups. However, the full power of the DSM approach is demonstrated by the comparable discriminating abilities of localized facial features, such as periorbital, perinasal, and perioral patches, and the correlation of DSM-based predictions and molecular findings. This study demonstrates the potential of face shape models to assist clinical training through visualization, to support clinical diagnosis of affected individuals through pattern recognition, and to enable the objective comparison of individuals sharing other phenotypic or genotypic properties.

Dense surface point distribution models of the human face

In this paper we show how a dense surface model of the human face can be built from a population of examples. A technique that combines active shape models (ASMs) with iterative closest point (ICP) can be used to fit the model to new faces. The model is built by aligning the surfaces using a sparse set of hand-placed landmarks, then using thin-plate spline warping to make a dense correspondence with a base mesh. All of the mesh vertices are then used as landmarks to build a 3D point distribution model. The dense surface point distribution model is more sensitive than the landmark model to correlated facial characteristics such as gender, age and the presence of congenital abnormalities.

Evolvable self-replicating molecules in an artificial chemistry

This paper gives details of Squirm3, a new artificial environment based on a simple physics and chemistry that supports self-replicating molecules somewhat similar to DNA. The self-replicators emerge spontaneously from a random soup given the right conditions. Interactions between the replicators can result in mutated versions that can outperform their parents. We show how artificial chemistries such as this one can be implemented as a cellular automaton. We concur with Dittrich, Ziegler, and Banzhaf that artificial chemistries are a good medium in which to study early evolution.

Evolvable Self-Reproducing Cells in a Two-Dimensional Artificial Chemistry

We present a novel unit of evolution: a self-reproducing cell in a two-dimensional artificial chemistry. The cells have a strip of genetic material that is used to produce enzymes, each catalyzing a specific reaction that may affect the survival of the cell. The enzymes are kept inside the cell by a loop of membrane, thus ensuring that only the cell that produced them gets their benefit. A set of reaction rules, each simple and local, allows the cells to copy their genetic information and physically divide. The evolutionary possibilities of the cells are explored, and it is suggested that the system provides a useful framework for testing hypotheses about self-driven evolution.

Automated Registration of 3D Faces using Dense Surface Models

Dense surface models can be used to register unseen surfaces, using an algorithm which is a hybrid of iterative closest-point (ICP) and active shape model (ASM) fitting. In this paper we give details of this procedure and show how it can be improved by sequentially extending the transform group over which it operates. We also evaluate it for robustness to the position of the target and to shape variation across a set of unseen examples. The fit was successful on all 21 examples in our test set, with an average RMS error of 3.0mm. An initial comparison of 3 people landmarking the same scans suggests that this is within the normal landmark reproducibility range for 3D face scans.

The organic builder: A public experiment in artificial chemistries and self-replication

We describe some results submitted by users of the Organic Builder, a Java applet where the rules of an artificial chemistry can be chosen in order to achieve a desired behavior. Though it was initially intended as a set of challenges to be tackled as a game, the users experimented with the system far beyond this and discovered several novel forms of self-replicators. When searching for a system with certain properties such as self-replication, making the system accessible to the public through a Web site is an unusual but effective way of making scientific discoveries, credit for which must go to the users themselves for their tireless experimentation and innovation.

Codd's self-replicating computer

Edgar Codds 1968 design for a self-replicating cellular automaton has never been implemented. Partly this is due to its enormous size, but we have also identified four problems with the original specification that would prevent it from working. These problems potentially cast doubt on Codds central assertion, that the eight-state space he presents supports the existence of machines that can act as universal constructors and computers. However, all these problems were found to be correctable, and we present a complete and functioning implementation after making minor changes to the design and transition table. The body of the final machine occupies an area that is 22,254 cells wide and 55,601 cells high, composed of over 45 million nonzero cells in its unsheathed form. The data tape is 208 million cells long, and self-replication is estimated to take at least 1.7 1018 time steps.

Combining biometric and symbolic models for customised, automated prosthesis design

In a previous paper [Artif. Intell. Med. 5 (1993) 431] we described RaPiD, a knowledge-based system for designing dental prostheses. The present paper discusses how RaPiD has been extended using techniques from computer vision and logic grammars. The first employs point distribution and active shape models (ASMs) to determine dentition from images of casts of patients jaws. This enables a design to be customized to, and visualised against, an image of a patients dentition. The second is based on the notion of a path grammar, a form of logic grammar, to generate a path linking an ordered sequence of subcomponents. The shape of an important and complex prosthesis component can be automatically seeded in this fashion. Combining these models now substantially automates the design process, beginning with a photograph of a dental cast and ending with an annotated and validated design diagram ready to guide manufacture.