Abstract
This paper presents the results of the research project BurnCase in the field of realistic and anatomically correct deformations of 3D models of the human body. The project goal is to develop a software system named BurnCase 3D, which supports and enhances the documentation and diagnosis of human burn injuries.
The medical treatment of burn victims strongly depends on size, depth, degree and location of the burnt skin. The size of the affected region is usually expressed as a percentage of the total body surface area (TBSA). Standardized 2D charts (e.g. Lund and Browder, Rule-Of-Nines, etc.) help to determine the percentage of the burnt surface area in relation to the total body surface area. However, body proportions highly influence the distribution of body surface area along the body [Livingston and Lee, 2000]. Thus, standard charts can only give rough approximations of the burnt surface area compared to the real size of an injury on a specific patient.
The software system BurnCase 3D will enhance this commonly applied 2D approximation process by introducing a 3D model of the patient’s body. This 3D model provides a higher accordance to the real patient’s surface area than any 2D chart does and allows determining the burnt surface areas more exactly. BurnCase 3D is based on an extendable library of currently 7 standard models representing different sex, age and body shape. In order to meet the physical constitution of the real patient, the best fitting model is chosen and has to be adapted according to the patient’s height and weight. There exist several possibilities of adapting a 3D model to these parameters. This paper describes the three methods of body adaptations that are realized in the software system BurnCase 3D based on the thesis of Doris Siegl ([Siegl, 2003]).
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© 2004 Springer-Verlag Berlin Heidelberg
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Dirnberger, J., Giretzlehner, M., Luckeneder, T., Siegl, D., Haller, H.L., Rodemund, C. (2004). BurnCase 3D – Realistic Adaptation of 3-Dimensional Human Body Models. In: Barillot, C., Haynor, D.R., Hellier, P. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2004. MICCAI 2004. Lecture Notes in Computer Science, vol 3217. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30136-3_45
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DOI: https://doi.org/10.1007/978-3-540-30136-3_45
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