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Conference 13006 > Paper 13006-38
Paper 13006-38

Order-specific removal of nonlinearity from optical coherence tomography signals (Invited Paper)

10 April 2024 • 10:40 - 11:10 CEST | Etoile B, Niveau/Level 1

Abstract

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.

Presenter

Sylwia M. Kolenderska
Nicolaus Copernicus Univ. (Poland), Univ. of Canterbury (New Zealand)
Sylwia received her PhD from the Nicolaus Copernicus University in Torun (Poland) in 2015. After a 5-year-long postdoctoral position at the University of Auckland (New Zealand), she became an Adjunct Apointee at the University of Canterbury (also New Zealand) in 2021. Having been awarded MBIE Endevour funding in 2023, she continues her independent studies into advancing the capabilities of Optical Coherence Tomography using artificial intelligence by mainly focusing on enhancing the very process of OCT image calculation.
Application tracks: AI/ML
Author
Univ. of Canterbury (New Zealand)
Author
Univ. of Canterbury (New Zealand)
Presenter/Author
Sylwia M. Kolenderska
Nicolaus Copernicus Univ. (Poland), Univ. of Canterbury (New Zealand)