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

Mesh-to-raster based non-rigid registration of multi-modal images

Region of interest (ROI) alignment in medical images plays a crucial role in diagnostics, procedure planning, treatment, and follow-up. Frequently, a model is represented as triangulated mesh while the patient data is provided from CAT scanners as pixel or voxel data. Previously, we presented a 2D method for curve-to-pixel registration. This paper contributes (i) a general mesh-to-raster (M2R) framework to register ROIs in multi-modal images; (ii) a 3D surface-to-voxel application, and (iii) a comprehensive quantitative evaluation in 2D using ground truth provided by the simultaneous truth and performance level estimation (STAPLE) method. The registration is formulated as a minimization problem where the objective consists of a data term, which involves the signed distance function of the ROI from the reference image, and a higher order elastic regularizer for the deformation. The evaluation is based on quantitative light-induced fluoroscopy (QLF) and digital photography (DP) of decalcified teeth. STAPLE is computed on 150 image pairs from 32 subjects, each showing one corresponding tooth in both modalities. The ROI in each image is manually marked by three experts (900 curves in total). In the QLF-DP setting, our approach significantly outperforms the mutual information-based registration algorithm implemented with the Insight Segmentation and Registration Toolkit (ITK) and Elastix