Characterizing a material’s microstructure, especially as it relates to the manufacturing processes used to fabricate it, is of great interest to engineers and researchers. In recent years, state-of-the-art imaging techniques have been able to yield a plethora of high resolution 3D data that can be used to study materials at various length scales. This 3D data is usually organized as stacked serial sections of 2D images and almost always requires some combination of enhancement and segmentation (the process of separating an image into subsets), in order to extract meaningful information. To aid in this process, ModLayer was created as a MATLAB^® executable. ModLayer is an interactive graphical user interface that seeks to remove the burden of import/export redundancies when interacting with 3D data in MATLAB during visualization, modification, or segmentation through manual drawing across image stacks. The utility of ModLayer is demonstrated here through three case studies; (1) classifying regions of damage with in-situ time lapse X-ray micro-computed tomography (\(\mu \)-CT) of a glass fiber reinforced polypropylene (GFRP), (2) correcting multi-class segmentation errors in segmented X-ray \(\mu \)-CT images of a GRFP composite, and (3) capturing features of interest within in-situ 3D X-ray \(\mu \)-CT images during fatigue crack growth experiments of aluminum 7050. Overall, this tool is especially useful to engineers and researchers interested in correcting—within MATLAB—automated segmentation of noisy 3D images which can yield erroneous microstructural features in segmentation procedures.

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ModLayer：用于可视化和分类3D数据的MATLAB GUI图形分割工具

工程师和研究人员非常感兴趣的是表征材料的微观结构，尤其是涉及与制造该材料的制造过程有关的微观结构。近年来，最先进的成像技术已能够产生大量高分辨率3D数据，这些数据可用于研究各种长度尺度的材料。这种3D数据通常组织为2D图像的堆叠串行部分，并且几乎总是需要增强和分段（将图像分离为子集的过程）的某种组合，以便提取有意义的信息。要在此加工助剂，ModLayer被创建为MATLAB ^®可执行文件。ModLayer是一个交互式的图形用户界面，旨在通过可视化，修改或通过跨图像堆栈的手动分割在MATLAB中与3D数据进行交互时，消除导入/导出冗余的负担。这里通过三个案例研究来证明ModLayer的实用性。（1）使用玻璃纤维增​​强聚丙烯（GFRP）的原位延时X射线微计算机断层扫描（\（\ mu \） -CT）对损坏区域进行分类，（2）校正GRFP复合材料的分段X射线\（\ mu \）- CT图像，以及（3）在原位3D X射线\（\ mu \）内捕获感兴趣的特征-7050在铝7050的疲劳裂纹扩展实验期间的-CT图像。总体而言，该工具对于有兴趣在MATLAB内校正自动3D噪声图像的分割的工程师和研究人员特别有用，这些噪声会在分割过程中产生错误的微观结构特征。