A Virtual Surgical Training System that Simulates Cutting of Soft Tissue Using a Modified Pre-computed Elastic Model

A Virtual Surgical Training System that Simulates Cutting of Soft Tissue Using a Modified Pre-computed Elastic Model
Title:
A Virtual Surgical Training System that Simulates Cutting of Soft Tissue Using a Modified Pre-computed Elastic Model
Other Titles:
37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2015)
Keywords:
Publication Date:
25 August 2015
Citation:
K. K. Toe et al., "A virtual surgical training system that simulates cutting of soft tissue using a modified pre-computed elastic model," 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Milan, 2015, pp. 3695-3698. doi: 10.1109/EMBC.2015.7319195
Abstract:
This work presents a surgical training system that incorporates cutting operation of soft tissue simulated based on a modified pre-computed linear elastic model in the Simulation Open Framework Architecture (SOFA) environment. A pre-computed linear elastic model used for the simulation of soft tissue deformation involves computing the compliance matrix a priori based on the topological information of the mesh. While this process may require a few minutes to several hours, based on the number of vertices in the mesh, it needs only to be computed once and allows real-time computation of the subsequent soft tissue deformation. However, as the compliance matrix is based on the initial topology of the mesh, it does not allow any topological changes during simulation, such as cutting or tearing of the mesh. This work proposes a way to modify the pre-computed data by correcting the topological connectivity in the compliance matrix, without re-computing the compliance matrix which is computationally expensive.
License type:
PublisherCopyrights
Funding Info:
Description:
(c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
ISSN:
1094-687X
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