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Volume 171, 2014
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Non-negative matrix analysis for effective feature extraction in X-ray spectromicroscopy

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Abstract

X-Ray absorption spectromicroscopy provides rich information on the chemical organization of materials down to the nanoscale. However, interpretation of this information in studies of “natural” materials such as biological or environmental science specimens can be complicated by the complex mixtures of spectroscopically complicated materials present. We describe here the shortcomings that sometimes arise in previously-employed approaches such as cluster analysis, and we present a new approach based on non-negative matrix approximation (NNMA) analysis with both sparseness and cluster-similarity regularizations. In a preliminary study of the large-scale biochemical organization of human spermatozoa, NNMA analysis delivers results that nicely show the major features of spermatozoa with no physically erroneous negative weightings or thicknesses in the calculated image.

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Publication details

The article was received on 27 Feb 2014, accepted on 28 Apr 2014 and first published on 28 Apr 2014


Article type: Paper
DOI: 10.1039/C4FD00023D
Author version available: Download Author version (PDF)
Citation: Faraday Discuss., 2014,171, 357-371
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    Non-negative matrix analysis for effective feature extraction in X-ray spectromicroscopy

    R. Mak, M. Lerotic, H. Fleckenstein, S. Vogt, S. M. Wild, S. Leyffer, Y. Sheynkin and C. Jacobsen, Faraday Discuss., 2014, 171, 357
    DOI: 10.1039/C4FD00023D

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