Paper
2 October 2003 Optical coherence tomography evaluating the random tissues based on dynamical processing the stochastic low-coherence interference fringes
Erkki Alarousu, Igor P. Gurov, Jukka Hast, Risto Myllyla, Tuukka Prykari, Alexey Zakharov
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Abstract
Interferometers with a low-coherent illumination allow non-contact evaluating random tissues by locating the visibility maxima of interference fringes. The problem is the light scattering by a tissue, it is why interference fringe parameters are randomly varied. Other problem consists in the need to process large amount of data obtained in optical coherence tomography (OCT) systems. We propose to use a stochastic fringe model and Kalman filtering method for noisy low-coherence fringe processing. A fringe signal value is predicted at a next discretization step using full information available before this step and a prediction error is used for dynamic correction of fringe envelope, frequency and phase. The advantages of Kalman filtering method consist in its noise-immunity, high-speed data processing and optimal evaluation of fringe parameters. Specially fabricated random tissues have been measured with a low-coherence interferometer. The obtained data from the tissue internal structure are evaluated using a dynamic stochastic fringe processing algorithm applied to fringe signal samples series. Nonlinear Kalman filtering method was applied to measure scattering liquid velocity profile in the Doppler OCT. The measurement results are in good agreement with the results obtained by the Fourier transform method.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Erkki Alarousu, Igor P. Gurov, Jukka Hast, Risto Myllyla, Tuukka Prykari, and Alexey Zakharov "Optical coherence tomography evaluating the random tissues based on dynamical processing the stochastic low-coherence interference fringes", Proc. SPIE 5140, Optical Coherence Tomography and Coherence Techniques, (2 October 2003); https://doi.org/10.1117/12.500685
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KEYWORDS
Filtering (signal processing)

Nonlinear filtering

Tissues

Electronic filtering

Stochastic processes

Optical coherence tomography

Liquids

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