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Automatic Quantitative Image Analysis of Micrographs

机译:微图的自动定量图像分析

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Routine use of 3D characterization of SOFCs by focused ion beam (FIB) serial sectioning is generally restricted by the time consuming task of manually delineating structures within each image slice. We apply advanced image analysis algorithms to automatically segment the porosity phase of an SOFC anode in 3D. The technique is based on numerical approximations to partial differential equations to evolve a 3D surface to the desired phase boundary. Vector fields derived from the experimentally acquired data are used as the driving force. The two approaches are quantitatively compared and the automatic segmentation compared to manual delineation reveals a good correspondence. It is concluded that the automatic approach is more robust, more reproducible and orders of magnitude quicker than manual segmentation of SOFC anode porosity for subsequent quantitative 3D analysis. Lastly it is anticipated that the methodology can be extrapolated to all phases in the anode.
机译:通过聚焦离子束(FIB)串行切片的常规使用SOFC的3D表征通常限制在每个图像切片内手动描绘结构的耗时任务。我们应用高级图像分析算法以自动分段3D中的SOFC阳极的孔隙率相位。该技术基于数值近似到部分微分方程,以将3D表面扩展到所需的相位边界。从实验所获取的数据导出的传染媒介字段用作驱动力。两种方法是定量比较的,与手动描绘相比,自动分割显示出良好的对应关系。得出结论,自动方法比SOFC阳极孔隙率的手动分割更快,更可重复和数量级,用于随后的定量3D分析。最后,预计该方法可以将其推断为阳极中的所有阶段。

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