Automated Autofluorescence Background Subtraction Algorithm for Biomedical Raman Spectroscopy
Vancouver Coastal Health · University of British Columbia · +1 more institution
Abstract
A significant advantage of Raman spectroscopy as a noninvasive optical technique is its ability to detect subtle molecular or biochemical signatures within tissue. One of the major challenges for biomedical Raman spectroscopy is the removal of intrinsic autofluorescence background signals, which are usually a few orders of magnitude stronger than those arising from Raman scattering. A number of methods have been proposed for fluorescence background removal including excitation wavelength shifting, Fourier transformation, time gating, and simple or modified polynomial fitting. The single polynomial and the modified multi-polynomial fitting methods are relatively simple and effective, and thus are widely used in…
Citation impact
- FWCI
- 11.42
- Percentile
- 100%
- References
- 28
Authors
4- JZJianhua ZhaoCorresponding
Vancouver Coastal Health, University of British Columbia, Vancouver Coastal Health Research Institute
- HLHarvey Lui
Vancouver Coastal Health, University of British Columbia, Vancouver Coastal Health Research Institute
- DIDavid I. McLean
Vancouver Coastal Health, University of British Columbia, Vancouver Coastal Health Research Institute
- HZHaishan Zeng
Vancouver Coastal Health, University of British Columbia, Vancouver Coastal Health Research Institute
Topics & keywords
- Autofluorescence
- Raman spectroscopy
- Polynomial
- SIGNAL (programming language)
- Background subtraction
- Biological system
- Raman scattering
- Fourier transform