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Mesh Smoothing Algorithm Applied to a Finite Element Model of the Brain for Improved Brain-Skull Interface
Mireille E Kelley1, Logan E Miller, Jillian E Urban
1Wake forest University School of Medicine.
Biomedical Sciences Instrumentation
|May 22, 2015
Summary
Researchers created a smoothed finite element (FE) model of the brain and skull to improve head injury predictions. This enhanced model accurately represents the brain-skull interface for better impact analysis.
Area of Science:
- Biomechanics
- Computational Neuroscience
- Medical Imaging
Background:
- The brain-skull interface is critical for understanding head impact responses.
- Previous finite element (FE) models often have stair-stepped surfaces due to voxel-based construction, potentially affecting interface accuracy.
Purpose of the Study:
- To develop a smoothed FE model of the brain and skull.
- To enhance the accuracy of the brain-skull interface representation in FE models.
- To improve the prediction of head injuries.
Main Methods:
- A custom MATLAB code converted a brain atlas into a 1mm isotropic voxel-based FE model.
- A Laplacian non-shrinking smoothing algorithm was applied to refine model surfaces and interfaces.
- Element quality was assessed using warpage, Jacobian, aspect ratio, and skew.
Main Results:
- The smoothing algorithm successfully refined the stair-stepped surfaces of the voxel-based model.
- >99% of elements retained good quality after smoothing.
- The model accurately represents the brain, cerebrospinal fluid (CSF), ventricles, and skull.
Conclusions:
- Mesh smoothing significantly improves the representation of the brain-skull interface in FE models.
- The developed FE model provides a foundation for more accurate head injury prediction.
- Future work will incorporate contact definitions for advanced biomechanical simulations.
