Identification and removal of system-induced autofluorescence in miniaturized fiber-optic fluorescence endoscopes
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(Published version)
Date
2025
Authors
Xiang, L.
Chen, R.
Tan, J.T.M.
Nankivell, V.
Bursill, C.A.
McLaughlin, R.A.
Li, J.
Editors
Kafafi, Z.
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Journal article
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PNAS Nexus, 2025; 4(8):pgaf226-1-pgaf226-10
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Lei Xiang, Rouyan Chena, Joanne Tsui Ming Tan, Victoria Nankivell, Christina A. Bursill, Robert A. McLaughlin, and Jiawen Li
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Abstract
Miniaturized fiber-optic fluorescence endoscopes play a crucial role in medical diagnostics and research, but system-induced autofluorescence remains a significant challenge, particularly in single-fiber setups. While recent advances, such as double-clad fiber (DCF) and DCF couplers, have reduced background noise, complete elimination remains challenging. Research on the various sources of system-induced autofluorescence and the methods to remove them is scarce. This study seeks to fulfill this need by proposing practical approaches to the removal of system-induced autofluorescence. This study presents the methods to suppress static background noise and proposes an algorithm based on least-squares linear spectral unmixing to remove variable system-induced autofluorescence artifacts. The algorithm was evaluated on a single-fiber DCF intravascular imaging system, with phantom and rodent in vivo experiments confirming its effectiveness. Results showed accurate differentiation between true sample fluorescence and system-induced autofluorescence artifacts through the validation with optical coherence tomography images and histology results, further verified by statistical analysis. Unlike simple background subtraction, the method addresses both background noise and incidental artifacts, providing robust performance under varying conditions. Our method may be adapted to various fiber-based endoscopy setups and be compatible with different fluorescent agents and autofluorescence imaging, broadening its applicability in biomedical imaging.
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© The Author(s) 2025. Published by Oxford University Press on behalf of National Academy of Sciences. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.