Paper
23 March 2005 Data analysis in Raman measurements of biological tissues using wavelet techniques
Giovanni Maria Gaeta D.D.S., Flora Zenone, Carlo Camerlingo, Roberto Riccio D.D.S., Gianfranco Moro, Maria Lepore, Pietro Luigi Indovina
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Abstract
Raman spectroscopy of oral tissues is a promising tool for in vivo diagnosis of oral pathologies, due to the high chemical and structural information content of Raman spectra. However, measurements on biological tissues are usually hindered by low level signals and by the presence of interfering noise and background components due to light diffusion or fluorescence processes. Numerical methods can be used in data analysis, in order to overcome these problems. In this work the wavelet multicomponent decomposition approach has been tested in a series of micro-Raman measurements performed on “in vitro” animal tissue samples. The experimental set-up was mainly composed by a He-Ne laser and a monochromator equipped with a liquid nitrogen cooled CCD equipped with a grating of 1800 grooves/mm. The laser light was focused on the sample surface by means of a 50 X optical objective. The resulting spectra were analysed using a wavelet software package and the contribution of different vibration modes have been singled out. In particular, the C=C stretching mode, and the CH2 bending mode of amide I and amide III and tyrosine contributions were present. The validity of wavelet approach in the data treatment has been also successfully tested on aspirin.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Giovanni Maria Gaeta D.D.S., Flora Zenone, Carlo Camerlingo, Roberto Riccio D.D.S., Gianfranco Moro, Maria Lepore, and Pietro Luigi Indovina "Data analysis in Raman measurements of biological tissues using wavelet techniques", Proc. SPIE 5687, Lasers in Dentistry XI, (23 March 2005); https://doi.org/10.1117/12.593394
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Cited by 4 scholarly publications.
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KEYWORDS
Tissues

Raman spectroscopy

Wavelets

Signal processing

Discrete wavelet transforms

Proteins

Interference (communication)

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