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10 March 2020 Spectroscopic fingerprint stimulated Raman scattering imaging of living cells and large area tissues by ultrafast delay-line tuning and deep learning (Conference Presentation)
Haonan Lin
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Proceedings Volume 11252, Advanced Chemical Microscopy for Life Science and Translational Medicine; 1125215 (2020) https://doi.org/10.1117/12.2543903
Event: SPIE BiOS, 2020, San Francisco, California, United States
Abstract
Fingerprint stimulated Raman scattering (SRS) produces label-free chemical maps of molecules in living systems with higher specificity compared to CH vibration region. However, due to the weak signal levels in the fingerprint window, it remains challenging for fingerprint SRS to study highly dynamic or large-scale samples. Here, we push the design space of SRS using deep learning, which can recover the signal-to-noise ratio to the levels comparable to measurements with 100 times longer integration time. Combined with an ultrafast 50-kHz delay-line tuner, we can generate real-time images of cholesterol, fatty acid, and proteins of living cells and large-area tissues including the whole brain.
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Haonan Lin "Spectroscopic fingerprint stimulated Raman scattering imaging of living cells and large area tissues by ultrafast delay-line tuning and deep learning (Conference Presentation)", Proc. SPIE 11252, Advanced Chemical Microscopy for Life Science and Translational Medicine, 1125215 (10 March 2020); https://doi.org/10.1117/12.2543903
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KEYWORDS
Spectroscopy
Imaging spectroscopy
Raman scattering
Tissues
Raman spectroscopy
Signal to noise ratio
Ultrafast laser spectroscopy
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