Physically based soft tissue modeling is a state of the art in computer assisted surgery (CAS). But even such a sophisticated approach has its limits. The biomechanic behavior of soft tissue is highly complex, so that simplified models have to be applied. Under assumption of small deformations, usually applied in soft tissue modeling, soft tissue can be approximately described as a linear elastic continuum. Since there exist efficient techniques for solving linear partial differential equations, the linear elastic model allows comparatively fast calculation of soft tissue deformation and consequently the prediction of a patient's postoperative appearance. However, for the calculation of large deformations, which are not unusual in craniofacial surgery, this approach can implicate substantial error depending on the intensity of the deformation. The monitoring of the linearization error could help to estimate the scope of validity of calculations upon user defined precision. In order to quantify this error one even do not need to know the correct solution, since the linear theory implies the appropriate instruments for error detection in itself.
[1]
S. Cowin,et al.
Biomechanics: Mechanical Properties of Living Tissues, 2nd ed.
,
1994
.
[2]
Ralf Kornhuber,et al.
Adaptive Multilevel-Methods in 3-Space Dimensions.
,
1992
.
[3]
Peter Deuflhard,et al.
Concepts of an adaptive hierarchical finite element code
,
1989,
IMPACT Comput. Sci. Eng..
[4]
Gerhard A. Holzapfel,et al.
Nonlinear Solid Mechanics: A Continuum Approach for Engineering Science
,
2000
.
[5]
Philippe G. Ciarlet,et al.
The finite element method for elliptic problems
,
2002,
Classics in applied mathematics.
[6]
Evgeny Gladilin,et al.
Finite-Element Simulation of Soft Tissue Deformation
,
2000
.
[7]
F. Duck.
Physical properties of tissue
,
1990
.