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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Bibliographic Details
Published in:IEEE transactions on biomedical engineering Vol. 56; no. 5; pp. 1371 - 1382
Main Authors: Gobinet, Cyril, Vrabie, Valeriu, Manfait, Michel, Piot, Olivier
Format: Journal Article
Language:English
Published: United States IEEE 01.05.2009
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Biological system modeling
Biomedical optical imaging
Biopsy
Blind source separation
Dark current
Data Interpretation, Statistical
digital dewaxing
Humans
Instruments
Linear Models
Models, Biological
Optical detectors
Optical distortion
Optical mixing
Paraffin Embedding
paraffin-embedded skin biopsies
preprocessing
Principal Component Analysis
Raman spectroscopy
Signal Processing, Computer-Assisted
Skin
Skin - chemistry
Source separation
Specimen Handling
Spectrum Analysis, Raman
ISSN:0018-9294, 1558-2531, 1558-2531
Online Access:Get full text
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Summary: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