Non-negative matrix analysis for effective feature extraction in X-ray spectromicroscopy

Rachel Mak, Mirna Lerotic, Holger Fleckenstein, Stefan Vogt, Stefan M. Wild, Sven Leyffer, Yefim Sheynkin, Chris Jacobsen*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)357-371
Number of pages15
JournalFaraday Discussions
Volume171
DOIs
StatePublished - Dec 1 2014

ASJC Scopus subject areas

  • Physical and Theoretical Chemistry

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