Topological representation using combinatorial maps
Multiscale and a re-meshing approaches for real-time simulations of surgical cutting
Duration 01.10.2013 — now
Website USIAS project
Surgical procedures rely heavily on the experience of surgeons and therefore involves a number of risks. Computer-based simulation can reduce this risk as it is a strong candidate for surgical training, guidance and surgical robotics. A realistic simulation needs to take into account of soft tissue manipulations like cutting, tearing and needle insertion. Since these manipulations require an update of the topolocigal structure of an object – so-called topological changes – they are specifically challenging. In the following, we will explain how we face this challenge in the team MIMESIS.
The outcome of such surgical interventions is significantly affected by the microstructure of the material (discontinuities, holes, interfaces) remaining some of the most difficult surgical gestures to simulate. We are interested in the development of a numerical tool capable of the interactive simulation of surgical cutting using a multi-domain lattice-continuum approach. Around the cutting region, a mesoscopic discrete lattice approach suitable for initiation of cuts and subsequent tears is used. The remaining regions can be modeled by a continuum approach or through model reduction approaches based on pre-computations. The algorithms are implemented within the SOFA framework which is targets real-time computations, with an emphasis on medical simulation and the work is being performed within Legato team in direct collaboration with MIMESIS team.
The presentation can be found here.
Crack propagation within an heterogeneous medium
The final goal of this project is to simulate in real-time the cutting of heterogeneous of soft-tissues using two-scale model instead of using one macroscopic model as in Courtecuisse, H., Allard, J., Kerfriden, P., Bordas, S. P. a, Cotin, S., & Duriez, C. (2014). Real-time simulation of contact and cutting of heterogeneous soft-tissues. Medical Image Analysis, 18(2), 394–410. doi:10.1016/j.media.2013.11.001.
The work is partially funded by USIAS – University of Strasbourg Institute for Advanced Study. Details can be found here.