https://doi.org/10.1051/epjconf/202328713019
Raman signal extraction from BCARS intensity measurements using deep learning with a prior excitation profile
1 Department of Electronic Engineering, Maynooth University, Co. Kildare, Ireland
2 Department of Computer Science, Maynooth University, Maynooth, Co. Kildare, Ireland
3 Biosystems and Biomaterials Division, National Institute of Standards and Technology, Gaithersburg, MD, USA
* e-mail: ryan.muddiman.2021@mumail.ie
** e-mail: bryan.hennelly@mu.ie
Published online: 18 October 2023
Broadband Coherent anti-Stokes Raman Scattering (BCARS) microscopy is a useful technique for chemical analysis and allows the full vibrational fingerprint spectrum of a specimen to be obtained in millisec-onds. A major drawback to this technique is the presence of the non-resonant background response producing interference which prevents classical spectral analysis of the sample. Using a convolutional autoencoder and measurements of the laser characteristics, we have shown that it is possible to remove this background with-out requiring supervision, as is typically required for conventional removal methods. This approach therefore simplifies the analysis of hyperspectral images obtained with BCARS.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
