ModLayer: A MATLAB GUI Drawing Segmentation Tool for Visualizing and Classifying 3D Data
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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.
KeywordsThree-dimensional Characterization Image processing Segmentation
The authors gratefully acknowledge support from the National Science Foundation CMMI MoM, Award No. 1662554. Partial support for I.H. was provided by the NSF GRFP, Award Number DGE-1333468. The discontinuous fiber composite material was provided by Dr. Alan Wedgewood of Dupont, and the AA7050 fatigue data was provided by Steve Carter. The authors also acknowledge Xianghui Xiao for assisting with data acquisition at the Advanced Photon Source, the use of which was supported by the US Department of Energy, Office of Science, Office of Basic Energy Sciences, under Contract No. DE-AC02-06CH11357.
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Conflict of interest
The authors declare that they have no conflict of interest.
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