Characterization and subtraction of luminescence background signals in high‐wavenumber Raman spectra of human tissue. (2nd February 2018)

• Record Type: Journal Article
• Authors: Barroso, E.M.; Bakker Schut, T.C.; Caspers, P.J.; Santos, I.P.; Wolvius, E.B.; Koljenović, S.; Puppels, G.J.
• Is Part Of: Journal of Raman spectroscopy. Volume 49:Number 4(2018)
• Page Start: 699
• Page End: 709
• Publication Date: 2018-02-02
• Subjects: background estimation -- bleaching -- multiple regression fitting; Raman spectroscopy -- Periodicals; 535.846
• DOI: 10.1002/jrs.5338
• Languages: English
• ISSNs: 0377-0486

Abstract

Abstract: Raman spectroscopy in the high‐wavenumber spectral region (HWR) is particularly suited for fiber‐optic in vivo medical applications. The most‐used fiber‐optic materials have negligible Raman signal in the HWR. This enables the use of simple and cheap single‐fiber‐optic probes that can be fitted in endoscopes and needles. The HWR generally shows less tissue luminescence than the fingerprint region. However, the luminescence can still be stronger than the Raman signal. Hardware‐ and software‐based strategies have been developed to correct for these luminescence signals. Typically, hardware‐based strategies are more complex and expensive than software‐based solutions. Effective software strategies have almost exclusively been developed for the fingerprint region. First‐order polynomial baseline fitting (PBF) is the most common background/luminescence estimation employed for the HWR. The goal of this study was to characterize the luminescence background signals of HW spectra of human oral tissue and compare the performance of two algorithms for correction of these background signals: PBF and multiple regression fitting (MRF). In the MRF method, we introduce here, prior knowledge of the range of Raman signals that can be obtained from the tissues of interest is explicitly used. MRF is more robust than PBF because it does not require an a priori choice of the polynomial order for fitting the background signal. This is important because, as we show, no single polynomial order can optimally characterize all backgrounds that are encountered in HW tissue spectra. We conclude that MRF should be the preferred method for background subtraction in the HWR. Abstract : In this article, we present a new and effective method for correction of luminescent backgrounds in high‐wavenumber region Raman spectra. The method is based on multiple regression fitting and knowledge about the shape of luminescence‐free high‐wavenumber spectra.