ModLayer: A MATLAB GUI Drawing Segmentation Tool for Visualizing and Classifying 3D Data
ModLayer: A MATLAB GUI Drawing Segmentation Tool for Visualizing and Classifying 3D Data
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DOI：
10.1007/s40192-019-00160-5
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发表时间：
2019-11-06
影响因子：
3.3
通讯作者：
Sangid, Michael D.
中科院分区：
文献类型：
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作者：
Hanhan, Imad;Sangid, Michael D.
表征一种材料的微观结构，特别是当它与用于制造它的制造过程有关时，是工程师和研究人员非常感兴趣的。近年来，最先进的成像技术已经能够产生大量高分辨率的3D数据，这些数据可以用于研究不同长度尺度的材料。这种3D数据通常被组织为2D图像的堆叠的连续切片，并且几乎总是需要某种增强和分割的组合(将图像分成子集的过程)，以便提取有意义的信息。为了帮助实现这一过程，创建了作为可执行文件的MoLayer。MoLayer是一种交互式图形用户界面，旨在通过手动绘制图像堆栈，在可视化、修改或分割过程中与MATLAB中的3D数据交互时，消除导入/导出冗余的负担。通过三个案例研究，展示了该软件的实用性：(1)用玻璃纤维增强聚丙烯(GFRP)的原位时间推移X射线微CT(MU-CT)对损伤区域进行分类，(2)修正GRFP复合材料分段X射线MU-CT图像中的多类分割误差，以及(3)在铝7050的疲劳裂纹扩展实验中捕获原位3D X光MU-CT图像中感兴趣的特征。总体而言，该工具对工程师和研究人员特别有用，他们有兴趣在MatLab内纠正噪声3D图像的自动分割，这些图像可能会在分割过程中产生错误的微结构特征。
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 (R) 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.