Removing non-resonant background of CARS signal with generative adversarial network
Ziyi Luo,
Xiangcong Xu,
Danying Lin
et al.
Abstract:Coherent anti-Stokes Raman scattering (CARS) microscopy requires the removal of non-resonant background (NRB) to ensure spectral accuracy and quality. This study introduces a deep-learning-based algorithm that leverages its enhanced capability for NRB removal and spectra retrieval. A generative adversarial network is trained using simulated noisy CARS data, enabling straightforward analysis of real CARS spectra obtained from pork belly and living mice brains. The results highlight the algorithm's ability to ac… Show more
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