Details
| Original language | English |
|---|---|
| Pages (from-to) | 336-342 |
| Number of pages | 7 |
| Journal | Journal of Raman spectroscopy |
| Volume | 48 |
| Issue number | 2 |
| Publication status | Published - 2 Feb 2017 |
Abstract
In vivo Raman spectroscopy with low signal-to-noise ratio and strong, irregularly shaped fluorescence background imposes a challenge for automatic baseline correction methods. In this work, an approach that enables fast and efficient batch baseline correction has been developed, which is based on a morphological operation in combination with a mollifier algorithm. As this algorithm relies only on three parameters, which are determined by the given experimental conditions, it can be used for automatic and objective processing of many Raman spectra. The applicability of the baseline correction is demonstrated on resonance Raman spectra of beta-carotene mixed with fluorescent red ink as model system, on carotenoids in human skin, and on an excitation–emission map of the green alga Haematococcus pluvialis. In the future, the algorithm opens the potential for wide application in Raman spectra analysis in biological contexts. In particular, it greatly facilitates data processing in cases where special photochemical sample preparation or complex experimental baseline removal was required before. Similarly, processing data of experiments using resonant excitation techniques yielding strong fluorescence background is possible.
Keywords
- baseline correction, fluorescence removal, in vivo, mollifier, morphological
ASJC Scopus subject areas
- Materials Science(all)
- Chemistry(all)
- Spectroscopy
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In: Journal of Raman spectroscopy, Vol. 48, No. 2, 02.02.2017, p. 336-342.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Iterative morphological and mollifier-based baseline correction for Raman spectra
AU - Koch, Matthias
AU - Suhr, Christian
AU - Roth, Bernhard
AU - Meinhardt-Wollweber, Merve
N1 - Funding Information: This work was supported by the German Federal Ministry of Education and Research (BMBF) within the VIP-project MeDiOO (grant no. 03V0826).
PY - 2017/2/2
Y1 - 2017/2/2
N2 - In vivo Raman spectroscopy with low signal-to-noise ratio and strong, irregularly shaped fluorescence background imposes a challenge for automatic baseline correction methods. In this work, an approach that enables fast and efficient batch baseline correction has been developed, which is based on a morphological operation in combination with a mollifier algorithm. As this algorithm relies only on three parameters, which are determined by the given experimental conditions, it can be used for automatic and objective processing of many Raman spectra. The applicability of the baseline correction is demonstrated on resonance Raman spectra of beta-carotene mixed with fluorescent red ink as model system, on carotenoids in human skin, and on an excitation–emission map of the green alga Haematococcus pluvialis. In the future, the algorithm opens the potential for wide application in Raman spectra analysis in biological contexts. In particular, it greatly facilitates data processing in cases where special photochemical sample preparation or complex experimental baseline removal was required before. Similarly, processing data of experiments using resonant excitation techniques yielding strong fluorescence background is possible.
AB - In vivo Raman spectroscopy with low signal-to-noise ratio and strong, irregularly shaped fluorescence background imposes a challenge for automatic baseline correction methods. In this work, an approach that enables fast and efficient batch baseline correction has been developed, which is based on a morphological operation in combination with a mollifier algorithm. As this algorithm relies only on three parameters, which are determined by the given experimental conditions, it can be used for automatic and objective processing of many Raman spectra. The applicability of the baseline correction is demonstrated on resonance Raman spectra of beta-carotene mixed with fluorescent red ink as model system, on carotenoids in human skin, and on an excitation–emission map of the green alga Haematococcus pluvialis. In the future, the algorithm opens the potential for wide application in Raman spectra analysis in biological contexts. In particular, it greatly facilitates data processing in cases where special photochemical sample preparation or complex experimental baseline removal was required before. Similarly, processing data of experiments using resonant excitation techniques yielding strong fluorescence background is possible.
KW - baseline correction
KW - fluorescence removal
KW - in vivo
KW - mollifier
KW - morphological
UR - http://www.scopus.com/inward/record.url?scp=84982933544&partnerID=8YFLogxK
U2 - 10.15488/1215
DO - 10.15488/1215
M3 - Article
AN - SCOPUS:84982933544
VL - 48
SP - 336
EP - 342
JO - Journal of Raman spectroscopy
JF - Journal of Raman spectroscopy
SN - 0377-0486
IS - 2
ER -