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Proceedings Paper

Video-rate hyperspectral two-photon fluorescence microscopy for in vivo imaging
Author(s): Fengyuan Deng; Changqin Ding; Jerald C. Martin; Nicole M. Scarborough; Zhengtian Song; Gregory S. Eakins; Garth J. Simpson
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Paper Abstract

Fluorescence hyperspectral imaging is a powerful tool for in vivo biological studies. The ability to recover the full spectra of the fluorophores allows accurate classification of different structures and study of the dynamic behaviors during various biological processes. However, most existing methods require significant instrument modifications and/or suffer from image acquisition rates too low for compatibility with in vivo imaging. In the present work, a fast (up to 18 frames per second) hyperspectral two-photon fluorescence microscopy approach was demonstrated. Utilizing the beamscanning hardware inherent in conventional multi-photon microscopy, the angle dependence of the generated fluorescence signal as a function beam’s position allowed the system to probe of a different potion of the spectrum at every single scanning line. An iterative algorithm to classify the fluorophores recovered spectra with up to 2,400 channels using a custom high-speed 16-channel photon multiplier tube array. Several dynamic samples including live fluorescent labeled C. elegans were imaged at video rate. Fluorescence spectra recovered using no a priori spectral information agreed well with those obtained by fluorimetry. This system required minimal changes to most existing beam-scanning multi-photon fluorescence microscopes, already accessible in many research facilities.

Paper Details

Date Published: 20 February 2018
PDF: 9 pages
Proc. SPIE 10505, High-Speed Biomedical Imaging and Spectroscopy III: Toward Big Data Instrumentation and Management, 105050W (20 February 2018); doi: 10.1117/12.2286907
Show Author Affiliations
Fengyuan Deng, Purdue Univ. (United States)
Changqin Ding, Purdue Univ. (United States)
Jerald C. Martin, Purdue Univ. (United States)
Nicole M. Scarborough, Purdue Univ. (United States)
Zhengtian Song, Purdue Univ. (United States)
Gregory S. Eakins, Purdue Univ. (United States)
Garth J. Simpson, Purdue Univ. (United States)

Published in SPIE Proceedings Vol. 10505:
High-Speed Biomedical Imaging and Spectroscopy III: Toward Big Data Instrumentation and Management
Kevin K. Tsia; Keisuke Goda, Editor(s)

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