Computational Fluorescence Suppression in Shifted Excitation Raman Spectroscopy

Nia C. Jenkins, Katjana Ehrlich, Andras Kufcsak, Stephanos Yerolatsitis, Susan Fernandes, Irene Young, Katie Hamilton, Harry A.C. Wood, Tom Quinn, Vikki Young, Ahsan R. Akram, James M. Stone, Robert R. Thomson, Keith Finlayson, Kevin Dhaliwal, Sohan Seth

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Fiber-based Raman spectroscopy in the context of <italic>in vivo</italic> 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.

Original languageEnglish
Pages (from-to)2374-2383
Number of pages10
JournalIEEE Transactions on biomedical engineering
Issue number8
Early online date10 Feb 2023
Publication statusPublished - 31 Aug 2023

Bibliographical note

The authors thank the BioResource for access to tissue (NHS
Lothian BioResource, Scotland Research Ethics Service, reference
15/ES/0094). NCJ was supported through the University of Edinburgh
funding award. JMS, SY and HACW are supported through an
EPSRC fellowship (EP/S001123/1). SF is supported through an
MRC fellowship (MR/R017794/1). ARA is supported by a CRUK
Clinician Scientist Fellowship (A24867). NCJ and SS are with the
School of Informatics, University of Edinburgh, 10 Crichton Street,
Edinburgh, EH8 9AB, UK. (e-mails: {njenkin3,sohan.seth}
KE, AK, SF, IY, KH, TQ, VY, ARA, RRT, KF, KD, and SS are
with the Translational Healthcare Technology Group, Centre for
Inflammation Research, Queen’s Medical Research Institute,
University of Edinburgh, 47 Little France Crescent, Edinburgh, EH16
4TJ, UK. (e-mails: {Katjana.Ehrlich,A.Kufcsak,Susan.Fernandes,
iyoung3 K.Hamilton,tquinn,Vikki.Young,Ahsan.Akram,Keith.Finlayson,
Kev.Dhaliwal} SY, HACW. and JMS are with
the Centre for Photonics and Photonic Materials, University
of Bath, Claverton Down, Bath, BA2 7AY, UK. (emails:
{S.Yerolatsitis,H.Wood,J.M.Stone} RRT is with Scottish
Universities Physics Alliance (SUPA), Institute of Photonics and
Quantum Science, Heriot-Watt University, Edinburgh, EH144AS, UK.
(email: [email protected]).


The work of Nia C. Jenkins was supported by the University of Edinburgh. The work of James M. Stone, Stephanos Yerolatsitis, and Harry A. C. Wood was supported by EPSRC fellowship under Grant EP/S001123/1. The work of Susan Fernandes was supported by MRC fellowship under Grant MR/R017794/1. The work of Ahsan R. Akram was supported by the CRUK Clinician Scientist Fellowship under Grant A24867. The authors thank the BioResource for access to tissue (NHS Lothian BioResource, Scotland Research Ethics Service, reference 15/ES/0094).

FundersFunder number
Medical Research CouncilMR/R017794/1
Engineering and Physical Sciences Research CouncilEP/S001123/1
Cancer Research UKA24867, 15/ES/0094
University of Edinburgh


  • Biomedical
  • fluorescence
  • lung tissue
  • machine learning
  • optical fiber
  • raman spectroscopy
  • regularization
  • shifted excitation
  • smoothness
  • sparsity

ASJC Scopus subject areas

  • Biomedical Engineering


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