학술논문

Computational Fluorescence Suppression in Shifted Excitation Raman Spectroscopy
Document Type
Periodical
Source
IEEE Transactions on Biomedical Engineering IEEE Trans. Biomed. Eng. Biomedical Engineering, IEEE Transactions on. 70(8):2374-2383 Aug, 2023
Subject
Bioengineering
Computing and Processing
Components, Circuits, Devices and Systems
Communication, Networking and Broadcast Technologies
Raman scattering
Spectroscopy
Lung
Optical fibers
Smoothing methods
Optical scattering
Microscopy
Biomedical
fluorescence
lung tissue
machine learning
optical fiber
raman spectroscopy
regularization
shifted excitation
sparsity
smoothness
Language
ISSN
0018-9294
1558-2531
Abstract
Fiber-based Raman spectroscopy in the context of in vivo biomedical application suffers from the presence of background fluorescence from the surrounding tissue that might mask the crucial but inherently weak Raman signatures. One method that has shown potential for suppressing the background to reveal the Raman spectra is shifted excitation Raman spectroscopy (SER). SER collects multiple emission spectra by shifting the excitation by small amounts and uses these spectra to computationally suppress the fluorescence background based on the principle that Raman spectrum shifts with excitation while fluorescence spectrum does not. We introduce a method that utilizes the spectral characteristics of the Raman and fluorescence spectra to estimate them more effectively, and compare this approach against existing methods on real world datasets.