Topological filtering for 3D microstructure segmentation
Topological filtering for 3D microstructure segmentation
复制标题
DOI：
10.1016/j.commatsci.2021.110920
复制
发表时间：
2021-04
影响因子：
3.3
通讯作者：
Anand V. Patel;T. Hou;Juan D. Beltran Rodriguez-;T. Dey;D. Birnie
中科院分区：
文献类型：
--
作者：
Anand V. Patel;T. Hou;Juan D. Beltran Rodriguez-;T. Dey;D. Birnie
层析成像是一种广泛使用的三维显微结构分析工具。然而，分析面临困难，因为组成材料产生相似的灰度值。有时，这会提示图像分割过程将像素/体素分配到错误的阶段（活性物质或孔隙）。因此，在微结构特性计算中引入了误差。在这项工作中，我们开发了一种基于拓扑持久性（一种用于拓扑数据分析的技术）的名为persplate的过滤算法来提高分割质量。评估滤波算法时面临的一个问题是，真实图像数据通常不具备微观结构特征的“真实值”。对于本研究，我们构建了已知地基真值的合成图像。在合成图像上，我们比较了用我们的persplatfilter和其他方法(如总变差（TV）和非局部均值（NL-means）计算的孔隙率和minkowski函数（体积和表面积）。此外，在真实的3D图像上，我们直观地将我们的过滤器提供的分割结果与TV和NL-means进行比较。实验结果表明，该平台在分割质量上有显著提高。
Tomography is a widely used tool for analyzing microstructures in three dimensions (3D). The analysis, however, faces difficulty because the constituent materials produce similar grey-scale values. Sometimes, this prompts the image segmentation process to assign a pixel/voxel to the wrong phase (active material or pore). Consequently, errors are introduced in the microstructure characteristics calculation. In this work, we develop a filtering algorithm calledPerSplatbased on topological persistence (a technique used intopological data analysis) to improve segmentation quality. One problem faced when evaluating filtering algorithms is that real image data in general are not equipped with the ‘ground truth’ for the microstructure characteristics. For this study, we construct synthetic images for which the ground-truth values are known. On the synthetic images, we compare the poretortuosityandMinkowski functionals(volume and surface area) computed with ourPerSplatfilter and other methods such as total variation (TV) and non-local means (NL-means). Moreover, on a real 3D image, we visually compare the segmentation results provided by our filter against TV and NL-means. The experimental results indicate thatPerSplatprovides a significant improvement in segmentation quality.