Bone Mass Distribution of the Distal Tibia in Normal, Osteopenic, and Osteoporotic Conditions: An Ex Vivo Assessment Using HR-pQCT, DXA, and Computational Modelling.

Osteoporosis leads to bone loss and structural deterioration, which increase the risk of fractures. The aim of this study was to characterize the three-dimensional (3D) bone mass distributions of the distal tibia in normal, osteopenic, and osteoporotic conditions. High-resolution peripheral quantitative computed tomography (HR-pQCT) of the 33 % of the distal tibia and local dual-energy X-ray absorptiometry were applied to 53 intact, fresh-frozen tibiae. The HR-pQCTs were graded to assign local T-scores and merged into three equally sized average normal, osteopenic, and osteoporotic surface models. Volumetric bone mineral density (vBMD) was determined using categorized T-scores, volumetric visualization, and virtual bore probes at the dia-, meta-, and epiphyseal sites (T-DIA, T-META, and T-EPI). We observed a distinct 3D bone mass distribution that was gradually uninfluenced by T-score categories. T-DIA was characterized by the lowest bone mass located in the medullary cavity and a wide homogenous cortex containing the maximum vBMD. The T-META showed decreased cortical thickness and maximal vBMD. At the T-EPI, the relatively low vBMD of the mostly trabecular bone was similar to the maximal cortical vBMD in this sub-region. Four trabecular regions of low bone mass were identified in the recesses. The bone content gradually decreased at all sites, whereas the pattern of bone mass distribution remained essentially unchanged, with the exception of disproportionate losses at T-DIA, T-META, and T-EPI that consistently showed increased endocortical, intracortical, and trabecular bone loss. Extra information can be obtained from the specific pattern of bone mass distribution, potential disproportionate bone losses, and method used

Lworld: An Animation System Based on Rewriting

Lworld is a computer graphics animation system based on L-systems, a parallel rewriting technique used primarily in computer graphics for plant modeling. Because rulebased programming is a powerful technique, we use it as a basis for a general-purpose animation system. We describe the architecture, the features, and the programming language of the animation system. It is particularly well suited to model fractal curves, plants, fractal landscapes, group animation, visualization, and evolutionary optimizations. Lworld allows users to create real-time animations as well as raytraced image sequences for further movie production. It is freely available, and runs on PCs

Towards Autonomous Synthetic Actors

This paper describes an animation approach with autonomous actors reacting to their environment and taking decisions based on perception systems, memory and reasoning. With such a system, we should be able to create simulations of situations such as virtual humans moving in a complex environment they may know and recognize, or playing ball games based on their visual and touching perception. In particular, the paper describes an animation approach where synthetic vision is used for navigation by a synthetic actor. The vision is the main channel of information between the actor and its environment and offers a universal approach to pass the necessary information from the environment to an actor in the problems of path searching, obstacle avoidance, and internal knowledge representation with learning and forgetting characteristics. For the general navigation problem, we propose a local and a global approach. In the global approach, a dynamic occupancy octree grid serves as global 3D visual memory and allows an actor to memorize the environment that he sees and to adapt it to a changing and dynamic environment. His reasoning process allows him to find 3D paths based on his visual memory by avoiding impasses and circuits. In the local approach, low level vision based navigation reflexes, normally performed by intelligent actors, are simulated. The local navigation model uses the direct input information from his visual environment to reach goals or subgoals and to avoid unexpected obstacles. A more complex example of vision-based tennis playing is also presented

Abstract Towards Autonomous Synthetic Actors

This paper describes an animation approach with autonomous actors reacting to their environment and taking decisions based on perception systems, memory and reasoning. With such a system, we should be able to create simulations of situations such as virtual humans moving in a complex environment they may know and recognize, or playing ball games based on their visual and touching perception. In particular, the paper describes an animation approach where synthetic vision is used for navigation by a synthetic actor. The vision is the main channel of information between the actor and its environment and offers a universal approach to pass the necessary information from the environment to an actor in the problems of path searching, obstacle avoidance, and internal knowledge representation with learning and forgetting characteristics. For the general navigation problem, we propose a local and a global approach. In the global approach, a dynamic occupancy octree grid serves as global 3D visual memory and allows an actor to memorize the environment that he sees and to adapt it to a changing and dynamic environment. His reasoning process allows him to find 3D paths based on his visual memory by avoiding impasses and circuits. In the local approach, low level vision based navigation reflexes, normally performed by intelligent actors, are simulated. The local navigation model uses the direct input information from his visual environment to reach goals or subgoals and to avoid unexpected obstacles. A more complex example of vision-based tennis playing is also presented

Integration of Optimization by Genetic Algorithms into an L-System-Based Animation System

In Computer Graphics L-systems represent a powerful rule-based language for modeling complex objects and their animation. However, designing objects and animations by rules is a difficult task, because designers often cannot foresee the consequences of rules. This is especially true for non-experts in the domain. Therefore, we propose to enhance an L-system based animation system with evolutionary features based on genetic algorithms (GAs). These features support the designers' task of interactively modeling objects and animations. Starting from an initial population of L-system-defined objects, the computer proposes iteratively new populations based on fitness value that are determined by the designers' creative or functional criteria. Moreover, automatic optimization of L-System-defined objects/animations is possible if an appropriate fitness function can be found for a given problem. We present a concept to integrate optimization by genetic algorithms into an L-system based animation system. Typical examples, such as automatic function optimization and creative interactive design of objects, illustrate our work