CUDB: An improved decomposition model for orthogonal pseudo-polyhedra

We present a new decomposition model for Orthogonal Pseudo-Polyhedra (OPP): the Compact Union of Disjoint Boxes. This model is an improved version of the Ordered Union of Disjoint Boxes model. Our model has many desirable features versus the OUDB, such as less storage size and a better efficiency in the connected-component labeling (CCL) process. CCL is a very important operation for manipulating volume data where multiple disconnected components that compose a volume need to be identify. We present the algorithms for conversion to and from the Extreme Vertices Model, which is closely related to the OUDB, and for CCL. The performance of the CUDB is experimentally analyzed with 2D and 3D datasets.Postprint (published version

Multi-scale Modeling of Trauma Injury

We develop a multi-scale high fidelity biomechanical and physiologically-based modeling tools for trauma (ballistic/impact and blast) injury to brain, lung and spinal cord for resuscitation, treatment planning and design of personnel protection. Several approaches have been used to study blast and ballistic/impact injuries. Dummy containing pressure sensors and synthetic phantoms of human organs have been used to study bomb blast and car crashes. Large animals like pigs also have been equipped with pressure sensors exposed to blast waves. But these methods do not anatomically and physiologically biofidelic to humans, do not provide full optimization of body protection design and require animal sacrifice. Anatomy and medical image based high-fidelity computational modeling can be used to analyze injury mechanisms and to optimize the design of body protection. This paper presents novel approach of coupled computational fluid dynamics (CFD) and computational structures dynamics (CSD) to simulate fluid (air, cerebrospinal fluid) solid (cranium, brain tissue) interaction during ballistic/blast impact. We propose a trauma injury simulation pipeline concept staring from anatomy and medical image based high fidelity 3D geometric modeling, extraction of tissue morphology, generation of computational grids, multiscale biomechanical and physiological simulations, and data visualization

An improved boundary extraction algorithm using a plane-sweep technique

Extracting the boundary of a 3D or a 2D image is a fundamental operation in several image processing related fields. In other fields as NC-data generation, obtaining the cutting areas of sculptured surfaces can be performed by first representing the surface using a regular grid model which is equivalent to a 2D binary image. There exist several approaches to extract the boundary of a 3D image. Most of them represent the extracted boundary as a collection of a large number of little triangular or quadrangular faces whereas few approaches give general orthogonal contours with the corresponding inclusion relationships. One of these approaches is based on a secondary model EVM and allows to obtain the orientation of the output primitives (edges and faces). It actually obtains, for each plane of the resulting B-Rep model, a set of oriented edges that have to be rearranged as contours and these contours have to be classified in order to have the corresponding inclusion relationships. These last two processes are performed in a simple brute force way. In this paper, we present an improved algorithm that processes all the edges of a plane and, following a plane-sweep based method, obtains the contours and the inclusion relationships. The presented algorithm can also be applied to extract the boundary of a 2D image.Postprint (published version

Compact union of disjoint boxes: An efficient decomposition model for binary volumes

This paper presents in detail the CompactUnion of Disjoint Boxes (CUDB), a decomposition modelfor binary volumes that has been recently but brieflyintroduced. This model is an improved version of aprevious model called Ordered Union of Disjoint Boxes(OUDB). We show here, several desirable features thatthis model has versus OUDB, such as less unitary basicelements (boxes) and thus, a better efficiency in someneighborhood operations. We present algorithms forconversion to and from other models, and for basiccomputations as area (2D) or volume (3D). We alsopresent an efficient algorithm for connected-componentlabeling (CCL) that does not follow the classical two-passstrategy. Finally we present an algorithm for collision (oradjacency) detection in static environments. We test theefficiency of CUDB versus existing models with severaldatasets.Peer ReviewedPostprint (published version

Skeletal representations of orthogonal shapes

Skeletal representations are important shape descriptors which encode topological and geometrical properties of shapes and reduce their dimension. Skeletons are used in several fields of science and attract the attention of many researchers. In the biocad field, the analysis of structural properties such as porosity of biomaterials requires the previous computation of a skeleton. As the size of three-dimensional images become larger, efficient and robust algorithms that extract simple skeletal structures are required. The most popular and prominent skeletal representation is the medial axis, defined as the shape points which have at least two closest points on the shape boundary. Unfortunately, the medial axis is highly sensitive to noise and perturbations of the shape boundary. That is, a small change of the shape boundary may involve a considerable change of its medial axis. Moreover, the exact computation of the medial axis is only possible for a few classes of shapes. For example, the medial axis of polyhedra is composed of non planar surfaces, and its accurate and robust computation is difficult. These problems led to the emergence of approximate medial axis representations. There exists two main approximation methods: the shape is approximated with another shape class or the Euclidean metric is approximated with another metric. The main contribution of this thesis is the combination of a specific shape and metric simplification. The input shape is approximated with an orthogonal shape, which are polygons or polyhedra enclosed by axis-aligned edges or faces, respectively. In the same vein, the Euclidean metric is replaced by the L infinity or Chebyshev metric. Despite the simpler structure of orthogonal shapes, there are few works on skeletal representations applied to orthogonal shapes. Much of the efforts have been devoted to binary images and volumes, which are a subset of orthogonal shapes. Two new skeletal representations based on this paradigm are introduced: the cube skeleton and the scale cube skeleton. The cube skeleton is shown to be composed of straight line segments or planar faces and to be homotopical equivalent to the input shape. The scale cube skeleton is based upon the cube skeleton, and introduces a family of skeletons that are more stable to shape noise and perturbations. In addition, the necessary algorithms to compute the cube skeleton of polygons and polyhedra and the scale cube skeleton of polygons are presented. Several experimental results confirm the efficiency, robustness and practical use of all the presented methods