کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1571001 | 1514392 | 2014 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
On the importance of FIB-SEM specific segmentation algorithms for porous media
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی مواد
دانش مواد (عمومی)
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: On the importance of FIB-SEM specific segmentation algorithms for porous media On the importance of FIB-SEM specific segmentation algorithms for porous media](/preview/png/1571001.png)
چکیده انگلیسی
A new algorithmic approach to segmentation of highly porous three dimensional image data gained by focused ion beam tomography is described which extends the key-principle of local threshold backpropagation described in Salzer et al. (2012). The technique of focused ion beam tomography has shown to be capable of imaging the microstructure of functional materials. In order to perform a quantitative analysis on the corresponding microstructure a segmentation task needs to be performed. However, algorithmic segmentation of images obtained with focused ion beam tomography is a challenging problem for highly porous materials if filling the pore phase, e.g. with epoxy resin, is difficult. The gray intensities of individual voxels are not sufficient to determine the phase represented by them and usual thresholding methods are not applicable. We thus propose a new approach to segmentation that pays respect to the specifics of the imaging process of focused ion beam tomography. As an application of our approach, the segmentation of three dimensional images for a cathode material used in polymer electrolyte membrane fuel cells is discussed. We show that our approach preserves significantly more of the original nanostructure than a thresholding approach.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Materials Characterization - Volume 95, September 2014, Pages 36-43
Journal: Materials Characterization - Volume 95, September 2014, Pages 36-43
نویسندگان
Martin Salzer, Simon Thiele, Roland Zengerle, Volker Schmidt,