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J Biophotonics. 2009 Feb;2(1-2):13-28. doi: 10.1002/jbio.200810024.

Disease recognition by infrared and Raman spectroscopy.

Author information

  • 1Bioanalytical Chemistry, Dresden University of Technology, 01062 Dresden, Germany. christoph.krafft@ipht-jena.de

Abstract

Infrared (IR) and Raman spectroscopy are emerging biophotonic tools to recognize various diseases. The current review gives an overview of the experimental techniques, data-classification algorithms and applications to assess soft tissues, hard tissues and body fluids. The methodology section presents the principles to combine vibrational spectroscopy with microscopy, lateral information and fiber-optic probes. A crucial step is the classification of spectral data by a variety of algorithms. We discuss unsupervised algorithms such as cluster analysis or principal component analysis and supervised algorithms such as linear discriminant analysis, soft independent modeling of class analogies, artificial neural networks support vector machines, Bayesian classification, partial least-squares regression and ensemble methods. The selected topics include tumors of epithelial tissue, brain tumors, prion diseases, bone diseases, atherosclerosis, kidney stones and gallstones, skin tumors, diabetes and osteoarthritis.

((c) 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim).

PMID:
19343682
[PubMed - indexed for MEDLINE]
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