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We present two neural networks: one capable of processing a raw spectrum into an A-scan with the second-order nonlinearity removed and another for processing a raw spectrum into an A-scan with the third-order nonlinearity removed. An algorithm is also proposed to enable to use these networks in a sequence for removal of both nonlinearities. The presented approaches allow for either independent switching off of each order or the simultaneous removal of all orders, offering a tool for analysing the effects of each nonlinearity order individually or simply for performing all-depth, blind OCT data linearisation.
Conference Presentation
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Krzysztof A. Maliszewski, Varvara Vetrova, Sylwia M. Kolenderska, "Order-specific removal of nonlinearity from optical coherence tomography signals," Proc. SPIE 13006, Biomedical Spectroscopy, Microscopy, and Imaging III, 130060I (20 June 2024); https://doi.org/10.1117/12.3016578