Preprocessing Methods of Raman Spectra for Source Extraction on Biomedical Samples: Application on Paraffin-Embedded Skin Biopsies

Raman spectra are classically modeled as a linear mixing of spectra of molecular constituents of the analyzed sample. Source separation methods are thus well suited to estimate these constituent spectra. However, physical distortions due to the instrumentation and biological nature of samples add no...

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Vydáno v:IEEE transactions on biomedical engineering Ročník 56; číslo 5; s. 1371 - 1382
Hlavní autoři: Gobinet, Cyril, Vrabie, Valeriu, Manfait, Michel, Piot, Olivier
Médium: Journal Article
Jazyk:angličtina
Vydáno: United States IEEE 01.05.2009
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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ISSN:0018-9294, 1558-2531, 1558-2531
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Shrnutí:Raman spectra are classically modeled as a linear mixing of spectra of molecular constituents of the analyzed sample. Source separation methods are thus well suited to estimate these constituent spectra. However, physical distortions due to the instrumentation and biological nature of samples add nonlinearities to the Raman spectra model. These distortions are dark current, detector and optic responses, fluorescence background, and peak misalignment and peak width heterogeneity. The source separation results are thus deteriorated by these effects. We propose to develop specific preprocessing steps to correct these distortions and to retrieve a linear model. The benefits brought by these steps are studied by the application of two different source separation methods named joint approximate diagonalization of eigenmatrices and maximum likelihood positive source separation after the application of each step on a dataset acquired on a paraffin-embedded human skin biopsy. The efficacy of these methods to separate Raman spectra is also discussed.
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ISSN:0018-9294
1558-2531
1558-2531
DOI:10.1109/TBME.2009.2014073