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Transport in Porous Media

, Volume 112, Issue 1, pp 105–116 | Cite as

A Method for Image Decomposition and Particle Quantification in Multiphase Systems

  • S. GüntherEmail author
  • S. Odenbach
Article

Abstract

X-ray tomography has proven to be an effective tool for three-dimensional analysis of particle deposition in deep bed filtration. A major challenge in terms of quantitative data evaluation of such tomographic images is the implementation of a reliable image decomposition method in quantifying the various materials in a filter bed which has been flooded with water and contains particle depositions. Therefore, a multistage method, based on basic image processing operations, has been developed to decompose grayscale images of multiphase systems into sets of concentrations for each phase. In that regard, the quantification of strong absorbing particles below the resolution limit is of particular interest in order to enable the detection of particle deposition sites at the beginning of a filtration process. The method was tested on three model samples, consisting of glass, molybdenum particles and polyurethane, as a substitute for water, with entrapped air. It could be shown that the particle concentration can be determined for all samples with a maximum error of 14.5 %.

Keywords

Image decomposition Particle quantification X-ray tomography Deep bed filtration Imaging 

Notes

Acknowledgments

This work was supported by Deutsche Forschungsgemeinschaft (DFG) within the Project OD18/20-1.

References

  1. Al-Abduwani, F.A.H., Farajzadeh, R., et al.: Filtration of micron-sized particles in granular media revealed by X-ray computed tomography. Rev. Sci. Instrum. 76(10), 103704 (2005). doi: 10.1063/1.2103467 CrossRefGoogle Scholar
  2. Alvarez, R.E., Macovski, A.: Energy-selective reconstructions in X-ray computerized tomography. Phys. Med. Biol. 21(5), 733–744 (1976). doi: 10.1088/0031-9155/21/5/002 CrossRefGoogle Scholar
  3. Brooks, R.A., Di Chiro, G.: Beam hardening in X-ray reconstructive tomography. Phys. Med. Biol. 21(3), 390–398 (1976). doi: 10.1088/0031-9155/21/3/004 CrossRefGoogle Scholar
  4. Cardinal, H.N., Fenster, A.: An accurate method for direct dual-energy calibration and decomposition. Med. Phys. 17(3), 327–341 (1990). doi: 10.1118/1.596512 CrossRefGoogle Scholar
  5. Chen, C., Lau, B.L.T., Gaillard, J.-F., et al.: Temporal evolution of pore geometry, fluid flow, and solute transport resulting from colloid deposition. Water Resour. Res. 45, W06416 (2009). doi: 10.1029/2008WR007252 Google Scholar
  6. Duda, R., Hart, P.E.: Pattern Classification and Scene Analysis. Willey, New York (1973)Google Scholar
  7. Feldkamp, L.A., Davis, L.C., Kress, J.W.: Practial cone beam algorithm. J. Opt. Soc. Am. A 1(6), 612–619 (1984). doi: 10.1364/JOSAA.1.000612 CrossRefGoogle Scholar
  8. Gaillard, J.-F., Chen, C., Stonedahl, S.H., et al.: Imaging of colloidal deposits in granular porous media by X-ray difference micro-tomography. Geophys. Res. Lett. 34, L18404 (2007). doi: 10.1029/2007GL030514 CrossRefGoogle Scholar
  9. Granton, P.V., et al.: Implementation of dual-and triple-energy cone-beam micro-CT for postreconstruction material decomposition. Med. Phys. 35(11), 5030–5042 (2008). doi: 10.1118/1.2987668 CrossRefGoogle Scholar
  10. Günther, D., Borin, D.Y., Günther, S., Odenbach, S.: X-ray micro-tomographic characterization of field-structured magnetorheological elastomers. Smart Mater. Struct. 21, 015005 (2012). doi: 10.1088/0964-1726/21/1/015005 CrossRefGoogle Scholar
  11. Haralick, R.M., Sternberg, S.R., Zhuang, X.: Image analysis using mathematical morphology. IEEE Trans. Pattern Anal. Mach. Intell. 4, 532–550 (1987). doi: 10.1109/TPAMI.1987.4767941 CrossRefGoogle Scholar
  12. Herman, G.T.: Correction for beam hardening in computed tomography. Phys. Med. Biol. 24(1), 81–106 (1979). doi: 10.1088/0031-9155/24/1/008 CrossRefGoogle Scholar
  13. Journel, A.G.: Constrained interpolation and soft kriging. In: Proceedings of the 19th APCOM Symposium, pp. 15–30 (1986)Google Scholar
  14. Köthe, U.: Generische Programmierung für die Bildverarbeitung. Ph.D. thesis, Universität Hamburg (2000)Google Scholar
  15. Kniss, J., Kindlmann, G., Hansen, C.: Multidimensional transfer functions for interactive volume rendering. IEEE Trans. Vis. Comput. Graph. 8(3), 270–285 (2002). doi: 10.1109/TVCG.2002.1021579 CrossRefGoogle Scholar
  16. Li, X., Lin, C.L., Miller, J.D., et al.: Pore-scale observation of microsphere deposition at grain-to-grain contacts over assemblage-scale porous media domains using X-ray microtomography. Environ. Sci. Technol. 40, 3762–3768 (2006). doi: 10.1021/es0525004 CrossRefGoogle Scholar
  17. McNear, D.H., Peltier, E., Everhart, J., Chaney, R.L., Sutton, S., Newville, M., Rivers, M., Sparks, D.L.: Application of quantitative fluorescence and absorption-edge computed microtomography to image metal compartmentalization in Alyssum murale. Environ. Sci. Technol. 39, 2210–2218 (2005). doi: 10.1021/es0492034 CrossRefGoogle Scholar
  18. Oh, W., Lindquist, W.B.: Image thresholding by indicator kriging. IEEE Trans. Pattern Anal. Mach. Intell. 21(7), 590–602 (1999). doi: 10.1109/34.777370 CrossRefGoogle Scholar
  19. Rahn, H., Alexiou, C., Trahms, L., Odenbach, S.: 3-Dimensional quantitative detection of nanoparticle content in biological tissue samples after local cancer treatment. J. Magn. Magn. Mater. 360, 92–97 (2014). doi: 10.1016/j.jmmm.2014.02.021 CrossRefGoogle Scholar
  20. Raven, C.: Numerical removal of ring artifacts in microtomography. Rev. Sci. Instrum. 69(8), 2978–2980 (1998). doi: 10.1063/1.1149043 CrossRefGoogle Scholar
  21. Shepard, D.: A two-dimensional interpolation function for irregularly-spaced data. In: Proceedings of the 1968 ACM national conference, pp. 517–524 (1968). doi: 10.1145/800186.810616
  22. Taschereau, R., Silverman, R.W., Chatziioannou, A.F.: Dual-energy attenuation coefficient decomposition with differential filtration and application to a microCT scanner. Phys. Med. Biol. 55(4), 1141–1155 (2010). doi: 10.1088/0031-9155/55/4/016 CrossRefGoogle Scholar
  23. Tsuchiyama, A., Uesugi, K., Nakano, T., Ikeda, S.: Quantitative evaluation of attenuation contrast of X-ray computed tomography images using monochromatized beams. Am. Mineral. 90, 132–142 (2005). doi: 10.2138/am.2005.1552 CrossRefGoogle Scholar
  24. Waske, A., Heiland, M., Beckmann, F. and Odenbach, S.: Absorption edge X-ray tomography for the analysis of particle deposition in packed bed filters. In: Porous media and its applications in science, engineering and industry: 3rd international conference, vol. 1254(1), pp. 187–192. AIP Publishing (2010). doi: 10.1063/1.3453808
  25. Waske, A., Heiland, M., Odenbach, S.: Local position of colloid clusters in a packed bed of spheres. Chem. Eng. Sci. 76, 192–198 (2012). doi: 10.1016/j.ces.2012.04.034 CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  1. 1.Institute of Fluid MechanicsTechnische Universität DresdenDresdenGermany

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