Connectivity-Preserving Cortical Surface Tetrahedralization

TL;DR

This paper introduces a new tetrahedralization method that preserves cortical surface connectivity despite defects, ensuring accurate biomechanical simulations and improving upon existing mesh generation techniques.

Contribution

The authors develop a novel tetrahedralization approach that maintains input surface connectivity even with mesh defects, along with a metric to evaluate connectivity preservation.

Findings

The method effectively preserves surface connectivity in defective meshes.

It outperforms existing solutions in maintaining connectivity.

The proposed metric accurately quantifies connectivity preservation.

Abstract

A prerequisite for many biomechanical simulation techniques is discretizing a bounded volume into a tetrahedral mesh. In certain contexts, such as cortical surface simulations, preserving input surface connectivity is critical. However, automated surface extraction often yields meshes containing self-intersections, small holes, and faulty geometry, which prevents existing constrained and unconstrained meshers from preserving this connectivity. We address this issue by developing a novel tetrahedralization method that maintains input surface connectivity in the presence of such defects. We also present a metric to quantify the preservation of surface connectivity and demonstrate that our method correctly maintains connectivity compared to existing solutions.