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Towards The Automatic Segmentation of Multiple Micro Analytical Maps

Published online by Cambridge University Press:  02 July 2020

N. Bonnet
N. Bonnet*
Affiliation:
University of Reims (INSERM U314), 21 rue Clément Ader, 51685, REIMS Cedex 2, France.
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Extract

Multi-dimensional data sets are now produced by many analytical instruments. They include the series of spectra, the series of images and spectrum-images, which can be considered as a series of spectra at different positions or series of images at different wavelengths.

The automatic (or semi-automatic) handling of such data sets requires that new multivariate analysis methods are made available. For instance, if we restrict ourselves to image sets, there is a need to deduce (from the multiple maps) a single map in which regions of the specimen with approximate homogeneous properties (composition ...) can be identified and quantified.

At the present time, only a limited number of software tools are available for this purpose: - the scatterplot allows the display of the correlations between two or three spectra or images, - Interactive Correlation Partitioning (ICP) allows the user to divide the scatterplot into several parts and to reconstitute images with one selected part, -Multivariate Statistical Analysis (MSA) allows us to analyze a data set composed of several images and to identify the different sources of information, and to filter out noise and experimental artefacts.

Type
Quantitative Analysis For Series of Spectra and Images: Getting The Most From Your Experimental Data
Information
Microscopy and Microanalysis , Volume 3 , Issue S2: Proceedings: Microscopy & Microanalysis '97, Microscopy Society of America 55th Annual Meeting, Microbeam Analysis Society 31st Annual Meeting, Histochemical Society 48th Annual Meeting, Cleveland, Ohio, August 10-14, 1997 , August 1997 , pp. 929 - 930
Copyright
Copyright © Microscopy Society of America 1997

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References

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Herbin, M., Bonnet, N., Vautrot, P., Pattern Recognition Letters 17(1996) 1141.10.1016/0167-8655(96)00085-2CrossRefGoogle Scholar