ASSESSMENT OF ULCER WOUNDS USING 3D SKIN SURFACE IMAGING

In medical care, ulcer wound refers to open wound or sore in which certain conditions exist that impede healing. Nonhealing wounds can cause economical and psychological distress for patients. Wound size measurement (top area, true surface area, depth, and volume) is an objective indicator for wound healing. Top area measurement is useful for the follow up of shallow wounds, while true surface area if done accurately can work for all types of wounds. Calculating ulcer volume is crucial since studies showed that wounds start healing from the bottom. Overestimation in top area and true surface area measurement can be solved by digitizing the traced part. The objective of this research is to develop computer algorithms to measure ulcer wound size using 3D surface imaging. The wounds of interest are the wounds located at the leg. The algorithms should construct wound models and compute volume without getting affected by irregularities on wound surface and they should model leg curvature. Two algorithms for constructing wound models and volume computation are developed and evaluated; namely midpoint projection and convex hull approximation (Delaunay tetrahedralization). Parameters that describe the wounds are developed based on real ulcer wound surface images for wound modelling. Wound models representing possible ulcer wounds developed using AutoCAD software are used to investigate the performance of solid reconstruction methods. Results and analysis show that, for volume computation midpoint and convex hull methods can compute volume of leg ulcer without getting affected by irregularities in the healthy skin around the wound. The results show that, for convex hull low errors are produced in cases of regular boundary models excluding the elevated base models. Overestimation in volume for convex hull method can either be due to irregular boundary and/or elevation at the base (both global and local). Surface division is performed prior to convex hull approximation so that the high curvature of the leg and irregularity at the boundary can be represented using a number of linear segments. With the increase in surface division, error due to irregular boundary is reduced. In the case of global curvature, the reconstructed model using convex hull preceded by surface division simulates the leg curvature. Midpoint outperforms convex hull for models excluding elevated base models. Midpoint can construct solids for wound surfaces with local curvature while for surfaces with high global curvature the error is high. Midpoint method is not suitable for shallow and very large wounds

ASSESSMENT OF ULCER WOUNDS USING 3D SKIN SURFACE IMAGING

In medical care, ulcer wound refers to open wound or sore in which certain conditions exist that impede healing. Nonhealing wounds can cause economical and psychological distress for patients. Wound size measurement (top area, true surface area, depth, and volume) is an objective indicator for wound healing. Top area measurement is useful for the follow up of shallow wounds, while true surface area if done accurately can work for all types of wounds. Calculating ulcer volume is crucial since studies showed that wounds start healing from the bottom. Overestimation in top area and true surface area measurement can be solved by digitizing the traced part. The objective of this research is to develop computer algorithms to measure ulcer wound size using 3D surface imaging. The wounds of interest are the wounds located at the leg. The algorithms should construct wound models and compute volume without getting affected by irregularities on wound surface and they should model leg curvature. Two algorithms for constructing wound models and volume computation are developed and evaluated; namely midpoint projection and convex hull approximation (Delaunay tetrahedralization). Parameters that describe the wounds are developed based on real ulcer wound surface images for wound modelling. Wound models representing possible ulcer wounds developed using AutoCAD software are used to investigate the performance of solid reconstruction methods. Results and analysis show that, for volume computation midpoint and convex hull methods can compute volume of leg ulcer without getting affected by irregularities in the healthy skin around the wound. The results show that, for convex hull low errors are produced in cases of regular boundary models excluding the elevated base models. Overestimation in volume for convex hull method can either be due to irregular boundary and/or elevation at the base (both global and local). Surface division is performed prior to convex hull approximation so that the high curvature of the leg and irregularity at the boundary can be represented using a number of linear segments. With the increase in surface division, error due to irregular boundary is reduced. In the case of global curvature, the reconstructed model using convex hull preceded by surface division simulates the leg curvature. Midpoint outperforms convex hull for models excluding elevated base models. Midpoint can construct solids for wound surfaces with local curvature while for surfaces with high global curvature the error is high. Midpoint method is not suitable for shallow and very large wounds

3D Object Reconstruction using Multi-View Calibrated Images

In this study, two models are proposed, one is a visual hull model and another one is a 3D object reconstruction model. The proposed visual hull model, which is based on bounding edge representation, obtains high time performance which makes it to be one of the best methods. The main contribution of the proposed visual hull model is to provide bounding surfaces over the bounding edges, which results a complete triangular surface mesh. Moreover, the proposed visual hull model can be computed over the camera networks distributedly. The second model is a depth map based 3D object reconstruction model which results a watertight triangular surface mesh. The proposed model produces the result with acceptable accuracy as well as high completeness, only using stereo matching and triangulation. The contribution of this model is to playing with the 3D points to find the best reliable ones and fitting a surface over them

Diamond-based models for scientific visualization

Hierarchical spatial decompositions are a basic modeling tool in a variety of application domains including scientific visualization, finite element analysis and shape modeling and analysis. A popular class of such approaches is based on the regular simplex bisection operator, which bisects simplices (e.g. line segments, triangles, tetrahedra) along the midpoint of a predetermined edge. Regular simplex bisection produces adaptive simplicial meshes of high geometric quality, while simplifying the extraction of crack-free, or conforming, approximations to the original dataset. Efficient multiresolution representations for such models have been achieved in 2D and 3D by clustering sets of simplices sharing the same bisection edge into structures called diamonds. In this thesis, we introduce several diamond-based approaches for scientific visualization. We first formalize the notion of diamonds in arbitrary dimensions in terms of two related simplicial decompositions of hypercubes. This enables us to enumerate the vertices, simplices, parents and children of a diamond. In particular, we identify the number of simplices involved in conforming updates to be factorial in the dimension and group these into a linear number of subclusters of simplices that are generated simultaneously. The latter form the basis for a compact pointerless representation for conforming meshes generated by regular simplex bisection and for efficiently navigating the topological connectivity of these meshes. Secondly, we introduce the supercube as a high-level primitive on such nested meshes based on the atomic units within the underlying triangulation grid. We propose the use of supercubes to associate information with coherent subsets of the full hierarchy and demonstrate the effectiveness of such a representation for modeling multiresolution terrain and volumetric datasets. Next, we introduce Isodiamond Hierarchies, a general framework for spatial access structures on a hierarchy of diamonds that exploits the implicit hierarchical and geometric relationships of the diamond model. We use an isodiamond hierarchy to encode irregular updates to a multiresolution isosurface or interval volume in terms of regular updates to diamonds. Finally, we consider nested hypercubic meshes, such as quadtrees, octrees and their higher dimensional analogues, through the lens of diamond hierarchies. This allows us to determine the relationships involved in generating balanced hypercubic meshes and to propose a compact pointerless representation of such meshes. We also provide a local diamond-based triangulation algorithm to generate high-quality conforming simplicial meshes