High Throughput Quantitative Raman Signal Extraction from Broadband Spectroscopic Coherent Anti-Stokes Raman Scattering (CARS) Hyperspectral Imagery

Charles H. Camp; John S. Bender; Young Jong Lee

doi:10.1364/COSI.2022.CW4B.5

Imaging and Applied Optics Congress 2022 (3D, AOA, COSI, ISA, pcAOP)
Technical Digest Series (Optica Publishing Group, 2022),
paper CW4B.5
•https://doi.org/10.1364/COSI.2022.CW4B.5

High Throughput Quantitative Raman Signal Extraction from Broadband Spectroscopic Coherent Anti-Stokes Raman Scattering (CARS) Hyperspectral Imagery

Charles H. Camp, John S. Bender, and Young Jong Lee

Computational Optical Sensing and Imaging 2022

Vancouver, British Columbia Canada
11–15 July 2022
ISBN: 978-1-957171-09-8

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Computational Spectroscopy and Spectral Imaging (CW4B)

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C. H. Camp, J. S. Bender, and Y. J. Lee, "High Throughput Quantitative Raman Signal Extraction from Broadband Spectroscopic Coherent Anti-Stokes Raman Scattering (CARS) Hyperspectral Imagery," in Imaging and Applied Optics Congress 2022 (3D, AOA, COSI, ISA, pcAOP), Technical Digest Series (Optica Publishing Group, 2022), paper CW4B.5.

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Abstract

Extraction of quantitative Raman signatures from BCARS spectra is fraught with challenges in computational time and spectral distortions. Here we present new linear methods that are capable of real-time performance and with significantly reduced error.

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