Label-free classification of T-cell differentiation via deep learning of hyperspectral stimulated Raman scattering microscopy images

Bryce Manifold; Ruoqian Hu; Elisa Clark; Hao Yuan Kueh; Dan Fu

doi:10.1117/12.2621455

27 May 2022 Label-free classification of T-cell differentiation via deep learning of hyperspectral stimulated Raman scattering microscopy images

Bryce Manifold, Ruoqian Hu, Elisa Clark, Hao Yuan Kueh, Dan Fu

Author Affiliations +

Proceedings Volume 12144, Biomedical Spectroscopy, Microscopy, and Imaging II; 1214406 (2022) https://doi.org/10.1117/12.2621455
Event: SPIE Photonics Europe, 2022, Strasbourg, France

Abstract

T cell differentiation has warranted intense study to understand the mechanisms behind the adaptive immune system. While much of the research so far has relied on antibody staining and flow cytometry separation to isolate and study T cells, we present hyperspectral stimulated Raman scattering (SRS) microscopy as a potential label-free imaging method to directly observe and characterize T cells. We show that a deep learning model can be trained to identify and classify T cell differentiations from hyperspectral SRS images with 99% accuracy. We also show that fluorescent T cells in lymph node tissue can be predicted from SRS images, demonstrating potential towards an entirely label-free in-situ imaging strategy. SRS microscopy augmented with deep learning shows strong promise towards label-free in situ observation of T Cells.

Conference Presentation

Citation Download Citation

Bryce Manifold, Ruoqian Hu, Elisa Clark, Hao Yuan Kueh, and Dan Fu "Label-free classification of T-cell differentiation via deep learning of hyperspectral stimulated Raman scattering microscopy images", Proc. SPIE 12144, Biomedical Spectroscopy, Microscopy, and Imaging II, 1214406 (27 May 2022); https://doi.org/10.1117/12.2621455

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