Controlling the Error on Target Motion Through Real-Time Mesh Adaptation: Applications to Deep Brain Stimulation

Authors

Huu Phuoc Bui
Satyendra Tomar
Hadrien Courtecuisse
M. Audette, Old Dominion UniversityFollow
Stéphane Cotin
Stéphane P.A. Bordas

Document Type

Article

Publication Date

2017

Publication Title

Frontiers

Pages

1-21

Abstract

We present an error-controlled mesh refinement procedure for needle insertion simulation and apply it to the simulation of electrode implantation for deep brain stimulation, including brain shift.

Our approach enables to control the error in the computation of the displacement and stress fields around the needle tip and needle shaft by suitably refining the mesh, whilst maintaining a coarser mesh in other parts of the domain.

We demonstrate through academic and practical examples that our approach increases the accuracy of the displacement and stress fields around the needle without increasing the computational expense. This enables real-time simulations.

The proposed methodology has direct implications to increase the accuracy and control the computational expense of the simulation of percutaneous procedures such as biopsy, brachytherapy, regional anesthesia, or cryotherapy and can be essential to the development of robotic guidance.

Comments

Published under a Creative Commons License CC BY-NC-ND 3.0.

From arXiv: http://arxiv.org/abs/1704.07636

ORCID

0000-0003-0011-1731 (Audette)

Repository Citation

Bui, Huu Phuoc; Tomar, Satyendra; Courtecuisse, Hadrien; Audette, M.; Cotin, Stéphane; and Bordas, Stéphane P.A., "Controlling the Error on Target Motion Through Real-Time Mesh Adaptation: Applications to Deep Brain Stimulation" (2017). Computational Modeling & Simulation Engineering Faculty Publications. 12.
https://digitalcommons.odu.edu/msve_fac_pubs/12