A Method for Increasing Precision and Reliability of Elasticity Analysis in Complicated Burn Scar Cases

Document Type

Article

Publication Date

2000

Keywords

Physically-based vision, deformable models, nonrigid motion analysis, active contours, biomedical applications, iterative descent search, finite element analysis

Digital Object Identifier (DOI)

https://doi.org/10.1142/S0218001400000131

Abstract

In this paper we propose a method for increasing precision and reliability of elasticity analysis in complicated burn scar cases. The need for a technique that would help physicians by objectively assessing elastic properties of scars, motivated our original algorithm. This algorithm successfully employed active contours for tracking and finite element models for strain analysis. However, the previous approach considered only one normal area and one abnormal area within the region of interest, and scar shapes which were somewhat simplified. Most burn scars have rather complicated shapes and may include multiple regions with different elastic properties. Hence, we need a method capable of adequately addressing these characteristics. The new method can split the region into more than two localities with different material properties, select and quantify abnormal areas, and apply different forces if it is necessary for a better shape description of the scar. The method also demonstrates the application of scale and mesh refinement techniques in this important domain. It is accomplished by increasing the number of Finite Element Method (FEM) areas as well as the number of elements within the area.

The method is successfully applied to elastic materials and real burn scar cases. We demonstrate all of the proposed techniques and investigate the behavior of elasticity function in a 3-D space. Recovered properties of elastic materials are compared with those obtained by a conventional mechanics-based approach. Scar ratings achieved with the method are correlated against the judgments of physicians.

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Citation / Publisher Attribution

International Journal of Pattern Recognition and Artificial Intelligence, v. 14, issue 2, p. 189-210

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