Twinsight
Digital Orthopedic Twins.
Adaptive meshing for numerical simulation in biomechanics.
COMPANY
Microflown Technologies
RESEARCH CENTRE
ITMATI & Universidade da Coruña
PRODUCTIVE SECTOR
Mechanics and Mechatronics
Problem description
Automatic finite element (FE) meshing of anatomical structures based on medical images is a complex procedure. The resulting meshes can produce inaccurate solutions due to the poor shape of some cells or a poor mesh resolution in some regions.
Challenges and goals
- Quantifying the discretization error
- 3D meshes from complex anatomical structures
- Sophisticated mathematical models.
Mathematical and computational methods
TwinSight creates accurate patient-specific numerical models for orthopedic surgery. These models are based on discretizations of anatomical structures from medical images, and use finite element analysis to predict the biomechanical behavior of bones and soft tissues.
These predictions are used by clinical staff to adjust therapeutic strategies, such as total knee replacement, so as to maximize functional performance and patient satisfaction. The TwinSight/CNRS collaboration aims at quantifying the error related to the discretization of the modeling domains and optimizing the mesh accordingly. This approach ensures that the numerical results are reliable while reducing the computational cost. The underlying mathematical tools used in the project are related to goal oriented a posteriori error estimates.
Results and Benefits
We have implemented goal oriented a posteriori error estimates for hyperelastic models of the soft tissue with active and passive constitutive laws. The underlying mathematical techniques form the cornerstone of the solution to the challenging modeling issue that the collaboration between TwinSight and the CNRS is tackling.
