Enhancement of signal-to-noise ratio for fluorescence endoscope image based on fast digital lock-in algorithm.

fast digital lock-in algorithm fluorescence endoscope image SNR tumour

Journal

Royal Society open science
ISSN: 2054-5703
Titre abrégé: R Soc Open Sci
Pays: England
ID NLM: 101647528

Informations de publication

Date de publication:
10 Mar 2021
Historique:
entrez: 7 5 2021
pubmed: 8 5 2021
medline: 8 5 2021
Statut: epublish

Résumé

In this paper, the signal-to-noise ratios (SNR) of two image channels were enhanced with the fast digital lock-in algorithm. In order to simultaneously improve the quality of white and fluorescence images obtained by fluorescence endoscope, and improve the SNR to achieve a better image processing effect, two sources of white light and near-infrared light of a fluorescence endoscope were modulated, then the acquired images were demodulated into white and fluorescence images. A fluorescent endoscope experimental platform was setup to acquire endoscopic images of a target dyed by indocyanine green. The experimental results showed that the SNR of white and fluorescent images without the lock-in algorithm were 36.56 dB and 33.47 dB, respectively. However, with the lock-in algorithm, the SNR of white and fluorescent images were 39.54 dB and 35.70 dB, respectively. The SNR of white and fluorescent images was increased by 8.2% and 6.7%, respectively, by appling the digital lock-in algorithm. Therefore, this novel fluorescence endoscope based on the fast digital lock-in algorithm can rapidly and simultaneously obtain two-channel images of white light and fluorescence, effectively enhance the SNR of white and fluorescent images, and improve the imaging quality.

Identifiants

pubmed: 33959306
doi: 10.1098/rsos.200779
pii: rsos200779
pmc: PMC8074948
doi:

Banques de données

figshare
['10.6084/m9.figshare.c.5324950']

Types de publication

Journal Article

Langues

eng

Pagination

200779

Informations de copyright

© 2021 The Authors.

Références

Mol Imaging. 2010 Oct;9(5):237-55
pubmed: 20868625
J Biomed Opt. 2013 May;18(5):57003
pubmed: 23652345
Mol Imaging Biol. 2011 Apr;13(2):199-207
pubmed: 20617389
J Biomed Opt. 2013 Oct;18(10):101302
pubmed: 23797876
J Biomed Opt. 2007 Mar-Apr;12(2):024017
pubmed: 17477732
Magn Reson Imaging Clin N Am. 2005 Aug;13(3):545-60
pubmed: 16084419
Rev Sci Instrum. 1979 Mar;50(3):296
pubmed: 18699495
Annu Rev Biomed Eng. 2010 Aug 15;12:119-42
pubmed: 20415592
Biomed Opt Express. 2014 Apr 29;5(5):1677-89
pubmed: 24877024
J Biomed Opt. 2013 Dec;18(12):126018
pubmed: 24362927
Clin Cancer Res. 2013 Jul 15;19(14):3745-54
pubmed: 23674494
Comput Aided Surg. 2002;7(6):317-25
pubmed: 12731094

Auteurs

Huiquan Wang (H)

School of Life Sciences, Tiangong University, Tianjin 300387, People's Republic of China.

Meng Hu (M)

School of Electronic and Information Engineering, Tiangong University, Tianjin 300387, People's Republic of China.

Fang Xia (F)

School of Life Sciences, Tiangong University, Tianjin 300387, People's Republic of China.

Meng Guo (M)

School of Life Sciences, Tiangong University, Tianjin 300387, People's Republic of China.

Shengzhao Zhang (S)

School of Biomedical Engineering, Anhui Medical University, Hefei 230032, People's Republic of China.

Zhe Zhao (Z)

School of Electronic and Information Engineering, Tiangong University, Tianjin 300387, People's Republic of China.

Guang Han (G)

School of Life Sciences, Tiangong University, Tianjin 300387, People's Republic of China.

Jinhai Wang (J)

School of Life Sciences, Tiangong University, Tianjin 300387, People's Republic of China.

Classifications MeSH