Research on meshing method for industrial CT volume data based on iterative smooth signed distance surface
ShiBo Jiang1,2, Shuo Xu1,2, YueWen Sun1,2
1Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing, China.
Journal of X-Ray Science and Technology
|February 20, 2025
Summary
This study introduces an improved method for meshing industrial CT volume data, enhancing efficiency and quality. The Iterative Smooth Signed Surface Distance (iSSD) algorithm ensures accurate, watertight 3D models for additive manufacturing and non-destructive testing.
Area of Science:
- Engineering
- Computer Science
- Materials Science
Background:
- Industrial Computed Tomography (CT) provides crucial 3D data for additive manufacturing and non-destructive testing.
- Converting 3D volume data to mesh models is essential for analysis, simulation, and editing.
- Existing Marching Cubes algorithms suffer from low efficiency and poor mesh quality.
Purpose of the Study:
- To develop an innovative and efficient method for meshing industrial CT volume data.
- To improve the quality and reliability of reconstructed mesh models.
- To overcome the limitations of existing meshing algorithms.
Main Methods:
- Proposes the Iterative Smooth Signed Surface Distance (iSSD) algorithm for volume data meshing.
- Refines segmented voxel models and extracts boundary voxels to create high-quality point clouds.
- Iteratively updates point cloud normals and reconstructs meshes using the SSD algorithm.
Main Results:
- Achieves high-quality, watertight, and smooth mesh model reconstruction.
- Demonstrates excellent performance compared to other methods through qualitative and quantitative analyses.
- Significantly improves the efficiency and quality of volume data meshing.
Conclusions:
- The iSSD algorithm provides a robust solution for industrial CT volume data meshing.
- The method enhances accuracy and reliability for subsequent 3D analysis and simulation.
- Presents important industrial application prospects and academic value.
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