Methods Inf Med 1992; 31(01): 29-35
DOI: 10.1055/s-0038-1634854
Original Article
Schattauer GmbH

Correspondence Analysis for Quantification in Electron Energy Loss Spectroscopy and Imaging

E. S. Gelsema
1   Department of Medical Informatics, The Netherlands
,
A. L. D. Beckers
1   Department of Medical Informatics, The Netherlands
,
C. W. J. Sorber
2   AEM Unit, Clinical Pathological Institute, Faculty of Medicine and Health Sciences, Erasmus University, Rotterdam, The Netherlands
,
W. C. de Bruijn
2   AEM Unit, Clinical Pathological Institute, Faculty of Medicine and Health Sciences, Erasmus University, Rotterdam, The Netherlands
› Author Affiliations
Further Information

Publication History

Publication Date:
08 February 2018 (online)

Abstract:

Electron energy loss spectroscopy (EELS) is a technique to investigate the physical properties of material. Using this technique it is possible to detect the presence of a specific element in a specimen. When used in combination with an electron microscope, energy filtered images may be obtained, which in principle may be used to quantify the local element concentration. This involves a process of background correction, conventionally performed assuming a specific parametric behavior of the spectral intensity as a function of electron energy loss. In this article a parameter-free method is described for background correction based on the formalism of correspondence analysis. Such a method may be used in parts of the spectrum where the functional dependence of the spectral intensity is unknown. Use of this method for element detection has been suggested before. This article reports simulation experiments suggesting its suitability for quantitative determination of element distributions and element concentrations.

 
  • REFERENCES

  • 1 Egerton RF. Energy Loss - Spectroscopy in the Electron Microscope. New York: Plenum Press; 1986
  • 2 Trebbia P, Bonnet N. EELS elemental mapping with unconventional methods. I. Theoretical basis: image analysis with multivariate statistics and entropy concepts. Ul-tramicroscopy 1990; 34: 165-78.
  • 3 Lebart L, Morineau A, Tabard N. Techniques de la Description Statistique. Paris: Dunod 1977
  • 4 Gelsema ES, Quieros C, Timmers T. The formalism of correspondence analysis as a means to describe object samples. In: Proc 6-th ICPR 1982; 564-8.
  • 5 Van Heel M. Finding the characteristic views of macromolecules in extremely noisy electron micrographs. In: Gelsema ES, Kanal LN. eds. Pattern Recognition in Practice II. Amsterdam: Elsevier Science Publ; 1986: 291-9.