In this work 3D surface scans of wounds are used to obtain several measurement including wound top area, true surface area (rue area), depth, and volume for the purpose of assessing the progress of ulcer wounds throughout treatment. KONICA MINOLTA 910 laser scanner is used to obtain the surface scans. The algorithm for estimating top area and true surface area from surface scan can reduce the inaccuracy that might result when using manual method. Two methods for solid construction and volume computation were considered; namely mid-point projection and convex hull approximation (Delaunay tetrahedralization). The performance of convex hull approximation method for volume estimation is improved by performing surface subdivision prior to the approximation. The performance of these algorithms on different patterns of simulated wound models is presented. Furthermore the algorithms are tested in two molded wounds printed using rapid prototyping (RP) technique.
Ulcer wound refers to a wound with underlying medical conditions that prevent healing. The ability to measure objectively early therapeutic response is important for wound management. Early therapeutic efficacy is best assessed by measurement of wound depth and volume. This study presents a non-invasive technique for assessing ulcer wound volume from three-dimensional (3D) surface scans. The accuracy of volume computation is dependent on the performance of the solid reconstruction of the wound. However, it is difficult to reconstruct solid models of wounds such as leg ulcers that extend over a large area along leg curvature and when irregularities exist on the skin surrounding the wound. The convex hull approximation preceded by surface division of the wound surface scan is proposed for solid reconstruction of wound models. This approach enables the reconstruction of models for large wounds without being affected by the surrounding irregularities. The performance of the algorithm is compared against reference volumes of wound models developed on AutoCAD. The best results are achieved using convex hull preceded by 20 surface divisions with volume computation error from 0 to 7%. Furthermore, moulds of wounds are developed to compute volumes using invasive and non-invasive methods, their percentage differences are below 8%.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.