AUTHOR=Zhang Shuyan , Chua Jian Jun , Tang Wilbert Yao Hwee , Cheng Joseph Yong Xin , Li Xiuting , Olivo Malini TITLE=An ultrathin fiber-based fluorescent imaging probe based on hyperspectral imaging JOURNAL=Frontiers in Physics VOLUME=10 YEAR=2023 URL=https://www.frontiersin.org/journals/physics/articles/10.3389/fphy.2022.1096290 DOI=10.3389/fphy.2022.1096290 ISSN=2296-424X ABSTRACT=

Most fluorescent imaging systems use pre-defined filter sets with limited flexibility in the choice of excitation and emission bands and suffer from crosstalk between different fluorophores for multiplexed imaging. When implemented in the context of optical fibers for biological imaging in a remote setting with space constraints, the size of the fiber probe is crucial. To overcome these challenges, we combined the merits of hyperspectral imaging and an ultrathin optical imaging fiber where fluorescent images at 311 spectral bands in the visible range were captured using a liquid crystal tunable filter with a fiber probe of 500 μm in diameter. Fluorescent experiments were performed on quantum dots mixtures and genetically modified E. coli bacteria mixtures to demonstrate the system’s capabilities for multiplexed imaging. Images were first processed using a Fourier transform filtering technique to remove the fiber core pattern artifact. Subsequently, the classification of different types of bacteria samples was calculated using two methods, namely, spectral unmixing with maximum abundance and spectral matching with minimum spectral angle distance. Finally, the spatial distributions of individual bacteria types were overlaid with the mixture image, and the two classification results matched well. A simple-to-use graphic user interface (GUI) platform for the hyperspectral imaging fiber probe system was developed which performs image processing and displays the classification results. The methods and results presented will appeal to the optical fiber-based imaging and hyperspectral imaging communities in general and have great potential for biological imaging applications.