Paper
28 May 2001 Validation of linear elastic model for soft tissue simulation in craniofacial surgery
Evgeny Gladilin, Stefan Zachow, Peter Deuflhard, Hans-Christian Hege
Author Affiliations +
Abstract
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.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Evgeny Gladilin, Stefan Zachow, Peter Deuflhard, and Hans-Christian Hege "Validation of linear elastic model for soft tissue simulation in craniofacial surgery", Proc. SPIE 4319, Medical Imaging 2001: Visualization, Display, and Image-Guided Procedures, (28 May 2001); https://doi.org/10.1117/12.428061
Lens.org Logo
CITATIONS
Cited by 11 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Tissues

Surgery

Error analysis

Bone

Finite element methods

Partial differential equations

Data modeling

Back to Top