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Proceedings Paper

Classification of Raman spectra of bacteria using rank order kernels
Author(s): Alexandros Kyriakides; Evdokia Kastanos; Katerina Hadjigeorgiou; Costas Pitris
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Paper Abstract

The range of applications of Raman-based classification has expanded significantly, including applications in bacterial identification. In this paper, we propose the use of Rank Order Kernels to classify bacterial samples. Rank Order Kernels are two-dimensional image functions which operate on two-dimensional images. The first step in the classification therefore, is to transform the Raman spectra to two-dimensional images. This is achieved by splitting the spectra into segments and calculating the ratio between the mean value of each and every other segment. This creates a two-dimensional matrix of ratios for each Raman spectrum. A similarity metric based on rank order kernels operating on the two-dimensional matrices is then used with a nearest neighbor algorithm for classification. Our results show that this method is comparable in accuracy to other methods which were used previously for the same data set.

Paper Details

Date Published: 22 March 2013
PDF: 8 pages
Proc. SPIE 8572, Advanced Biomedical and Clinical Diagnostic Systems XI, 85720Y (22 March 2013); doi: 10.1117/12.2003714
Show Author Affiliations
Alexandros Kyriakides, Univ. of Cyprus (Cyprus)
KIOS Research Ctr. for Intelligent Systems and Networks (Cyprus)
Evdokia Kastanos, Univ. of Nicosia (Cyprus)
Katerina Hadjigeorgiou, Univ. of Cyprus (Cyprus)
Costas Pitris, Univ. of Cyprus (Cyprus)
KIOS Research Ctr. for Intelligent Systems and Networks (Cyprus)


Published in SPIE Proceedings Vol. 8572:
Advanced Biomedical and Clinical Diagnostic Systems XI
Anita Mahadevan-Jansen; Tuan Vo-Dinh; Warren S. Grundfest, Editor(s)

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