Authors: Alois Bonifacio Claudia Beleites Valter Sergo
Publish Date: 2014/11/16
Volume: 407, Issue: 4, Pages: 1089-1095
Abstract
Hierarchical cluster analysis HCA is extensively used for the analysis of hyperspectral data In this work hyperspectral data sets obtained from Raman maps were analyzed using an alternative mode of cluster analysis clustering “images” instead of spectra under the assumption that images showing similar spatial distributions are related to the same chemical species Such an approach was tested with two Raman maps one simple “test map” of microcrystals of four different compounds for a proof of principle and a map of a biological tissue ie cartilage as an example of chemically complex sample In both cases the “imageclustering” approach gave similar results as the traditional HCA but at lower computational effort The alternative approach proved to be particularly helpful in cases as for the cartilage tissue where concentration gradients of chemical composition are present Moreover with this approach yielded information about correlation between bands in the average spectrum makes band assignment and spectral interpretation easier
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