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| Quantitative Measurement of 3D Skin Wound Area Based on Single Camera |
| Liu Chunhui1, Fan Yubo1,3*, Xu Yan1,2* |
1School of Biological Science and Medical Engineering,BUAA, State Key Laboratory of Software Development Environment and Key Laboratory of Biomechanics and Mechanobiology of Ministry of Education and Research Institute of Beihang University in Shenzhen, Beijing Advanced Innovation Center for Biomedical Engineering,Beijing 100191, China;
2Microsoft Research, Beijing 100080, China;
3National Research Center for Rehabilitation Technical Aids,Beijing100176, China |
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Abstract The measurement of skin wounds is an important work in the field of clinical research and forensic identification. Quantitative measurement of skin wounds area has important significance in forensic identification, clinical trials, the wound pathological analysis and daily patient care. In this paper, the algorithm of structure from motion (SFM) and least squares conformal mapping (LSCM) were introduced into the measurement of skin wounds area, combined with image segmentation, an algorithm that suitable for the area measurement of the human body surface was proposed. This paper used eigenvalue extraction, sparse reconstruction and dense reconstruction in order to get the 3D point cloud of the tested body. Then the paper used the Poisson reconstruction algorithm on the point to make them networked, and unwrap the UV map of the 3D model for skin wounds extraction and measurement in the end. This paper used the known area simulation wound as a benchmark, 40 groups were adopted to evaluate the accuracy of the algorithm. The measuring accuracy of the experimental results showed that the algorithm in this paper reached the accuracy of 0.97, compared with 2D measurement method, the accuracy was increased by 10.79%. The algorithm in this paper solved the shortcoming of the contact method and the problem of human curvature or angle deflection, which was hard to solve by the 2D measurement. In addition, the algorithm in this paper has less dependence of equipment and high accuracy especially in the parts with large curvature.
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Received: 01 June 2017
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