Materials Map

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (1/1 displayed)

  • 2008Automated registration for augmenting micro-CT 3D imagescitations

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Varslot, Trond
1 / 2 shared
Sheppard, Adrian
1 / 13 shared
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2008

Co-Authors (by relevance)

  • Varslot, Trond
  • Sheppard, Adrian
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article

Automated registration for augmenting micro-CT 3D images

  • Varslot, Trond
  • Latham, Shane Jamie
  • Sheppard, Adrian
Abstract

Micro-CT imaging allows probing of material 3D structure down to the micrometre scale. However, often there exists structure at the sub-micrometre scale which significantly influences the macro-physical properties of the material. One possible solution for mitigating this micro-CT resolution limitation is to incorporate information from higher resolution Back-scattered Scanning Electron Microscopy (BSEM) imaging techniques. A first step toward incorporating this high resolution data into micro-CT models is to align the BSEM 2D image(s) with the corresponding region(s) of the micro-CT 3D image. This article presents an automated multi-start multi-resolution parallel registration algorithm which has been successfully used to achieve accurate alignment of BSEM and micro-CT image pairs. References William H. Press, Brian P. Flannery, Saul A. Teukolsky, and William T. Vetterling. Numerical Recipes in {C}: The Art of Scientific Computing. Cambridge University Press, 2nd edition, October 1992. http://www.nrbook.com/a/bookcpdf.php B. Zitova and J. Flusser. Image registration methods: a survey. Image and Vision Computing, 21:977--1000, 2003. doi:{10.1016/S0262-8856(03)00137-9} L. G. Brown. A survey of image registration techniques. ACM Computing Surveys, 24:325--376, 1992. http://portal.acm.org/citation.cfm?id=146370.146374 Mark Jenkinson and Stephen Smith. A global optimisation method for robust affine registration of brain images. Medical Image Analysis, 5:143--156, June 2001. doi:{10.1016/S1361-8415(01)00036-6} C. D. Kuglin and D. C. Hines. The phase correlation image alignment method. In Proc. Int. Conf. on Cybernetics and Society, volume 4, pages 163--165, 1975. G.S. Padhy, C. Lemaire, E.S. Amirtharaj, and M.A. Ioannidis. Pore size distribution in multiscale porous media as revealed by {DDIF-NMR}, mercury porosimetry and statistical image analysis. Colloids and Surfaces A: Physicochemical and Engineering Aspects, 300:222--234, June 2007. doi:{10.1016/j.colsurfa.2006.12.039}

Topics
  • porous
  • impedance spectroscopy
  • pore
  • surface
  • phase
  • scanning electron microscopy
  • Nuclear Magnetic Resonance spectroscopy
  • porosimetry
  • Mercury
  • Chemical force microscopy