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Information Extraction: Statistical Analysis to Get the Most from Spectrum Images

Published online by Cambridge University Press:  02 July 2020

P. G. Kotula  and
M. R. Keenan
P. G. Kotula
Affiliation:
Sandia National Laboratories, Mail Stop 1405, P. O. Box 5800, Albuquerque, NM87185-1405
M. R. Keenan
Affiliation:
Sandia National Laboratories, Mail Stop 1405, P. O. Box 5800, Albuquerque, NM87185-1405
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Extract

As more x-ray energy dispersive spectroscopy (EDS) manufacturers begin to offer spectrum imaging (a complete x-ray spectrum from each pixel in an image), there is a clear need for robust and automated methods for quickly extracting the relevant information from the large spectrum image data sets. A typical spectrum image may consist of 100 x 100 pixels (10000 spectra) each with 1000 channels which (when stored at double precision) is 80 Mbytes. It is clear that a large four-dimensional data set such as this cannot be viewed in its entirety and the time to analyze individual spectra by hand is prohibitive. Conventional analysis of spectrum images by mapping energy windows is useful as a first pass only for finding the elements present and only if at sufficient concentrations. Additional problems with mapping include systematic overlaps of other x-ray peaks, changes in the background shape and displaying the maps so they faithfully portray the actual signal intensity.

Type
Spectrum Imaging: Applications and Methods of Analysis
Information
Microscopy and Microanalysis , Volume 6 , Issue S2: Proceedings: Microscopy & Microanalysis 2000, Microscopy Society of America 58th Annual Meeting, Microbeam Analysis Society 34th Annual Meeting, Microscopical Society of Canada/Societe de Microscopie de Canada 27th Annual Meeting, Philadelphia, Pennsylvania August 13-17, 2000 , August 2000 , pp. 1052 - 1053
Copyright
Copyright © Microscopy Society of America

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References

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