Paper Info
Title
Kalman-Based Real-Time Functional Decomposition for the Spectral Calibration in Swept Source Optical Coherence Tomography.
Abstract
This paper presents a real-time functional decomposition adaptive algorithm for the optimal sampling of the interferometric signal in Swept-Source Optical Coherence Tomography imaging systems, which completely eliminates the input signal dependent nonlinearities that are problematic in current state-of-the-art OCT realizations that use interpolation and resampling. The proposed adaptive calibration algorithm uses the Kalman approach to estimate the wavenumber index parameter <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$k$</tex-math></inline-formula> from the Mach-Zender Interferometer signal which is then applied to an adaptive level crossing sampler to generate a sampling clock that <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$k$</tex-math></inline-formula> -linearizes the data on real-time during the sampling process. Such a system implements an artifact-free realization of the technology removing the need for classical interpolation and resampling. The new real-time linearization scheme has the additional capability of increasing the imaging acquisition speed by 10X while providing robustness to noise, properties that are demonstrated through mathematical analysis and simulation results throughout the paper.
Year
DOI
Venue
2020
10.1109/TBCAS.2019.2953212
IEEE transactions on biomedical circuits and systems
Keywords
DocType
Volume
Kalman Filtering,Machine Learning,Mach-Zehnder Interferometer,Michelson Interferometer,Optical Coherence Tomography,Spectral Calibration,Swept Source Optical Coherence Tomography
Journal
14
Issue
ISSN
Citations 
2
1932-4545
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Amir Tofighi Zavareh122.04
Sebastian Hoyos223429.24