Optimization of Preliminary Vector Averaging for Improving Strain-Estimation Accuracy in Phase-Sensitive Optical Coherence Elastography

Alexey A. Zykov
A.V. Gaponov-Grekhov Institute of Applied Physics of the Russian Academy of Sciences, Nizhny Novgorod, Russia

Alexander L. Matveyev
A.V. Gaponov-Grekhov Institute of Applied Physics of the Russian Academy of Sciences, Nizhny Novgorod, Russia

Alexander A. Sovetsky
A.V. Gaponov-Grekhov Institute of Applied Physics of the Russian Academy of Sciences, Nizhny Novgorod, Russia

Vladimir Y. Zaitsev orcid (Login required)
A.V. Gaponov-Grekhov Institute of Applied Physics of the Russian Academy of Sciences, Nizhny Novgorod, Russia


Paper #9032 received 27 Oct 2023; revised manuscript received 24 Nov 2023; accepted for publication 24 Nov 2023; published online 26 Dec 2023.

DOI: 10.18287/JBPE23.09.040311

Abstract

In this paper we present a method that significantly improves strain estimation quality in phase-sensitive optical coherence elastography (OCE), in which interframe strains are proportional to gradients of interframe phase variations. The analyzed phase-sensitive OCT signals can be conveniently represented as complex-valued vectors, the arguments of which correspond to the sought interframe phase-variations. To reduce the noise influence on the strain-estimation accuracy, these complex-valued vectors are usually averaged over a certain window. Increase in the window size can greatly reduce the noise. At the same time, for inappropriately big windows, this smoothing may cause strong distortion of the reconstructed spatial distribution of strain in comparison with the actual distribution, especially in regions of large gradients of interframe phase variations and, correspondingly, increased strain level. Therefore, automatic adaptive choice of the window size is proposed to maximize the noise reduction and at the same time to avoid possible distortion of spatial strain distribution in the reconstructed strain maps.

Keywords

optical coherence elastography; OCE; automatic choice of parameters; adaptive averaging

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References


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