Optical coherence elastography based on inverse compositional Gauss-Newton digital volume correlation with second-order shape function

Hao Wu; Jiaqiu Wang; Jorge Alberto Amaya Catano; Cuiru Sun; Zhiyong Li

doi:10.1364/OE.473898

Optical coherence elastography based on inverse compositional Gauss-Newton digital volume correlation with second-order shape function

Hao Wu, Jiaqiu Wang, Jorge Alberto Amaya Catano, Cuiru Sun, Zhiyong Li

Research output: Contribution to journal › Article › peer-review

8 Citations (Scopus)

Abstract

A digital volume correlation (DVC)-based optical coherence elastography (OCE) method with inverse compositional Gauss-Newton (IC-GN) algorithm and second-order shape function is presented in this study. The systematic measurement errors of displacement and strain from our OCE method were less than 0.2 voxel and 4 × 10⁻⁴, respectively. Second-order shape function could better match complex deformation and decrease speckle rigidity-induced error. Compared to conventional methods, our OCE method could track a larger strain range up to 0.095 and reduce relative error by 30-50%. This OCE method has the potential to become an effective tool in characterising mechanical properties of biological tissue.

Original language	English
Pages (from-to)	41954-41968
Number of pages	15
Journal	Optics Express
Volume	30
Issue number	23
DOIs	https://doi.org/10.1364/OE.473898 https://doi.org/10.1364/OE.473898
Publication status	Published - 31 Oct 2022
Externally published	Yes

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© 2022 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

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title = "Optical coherence elastography based on inverse compositional Gauss-Newton digital volume correlation with second-order shape function",

abstract = "A digital volume correlation (DVC)-based optical coherence elastography (OCE) method with inverse compositional Gauss-Newton (IC-GN) algorithm and second-order shape function is presented in this study. The systematic measurement errors of displacement and strain from our OCE method were less than 0.2 voxel and 4 × 10−4, respectively. Second-order shape function could better match complex deformation and decrease speckle rigidity-induced error. Compared to conventional methods, our OCE method could track a larger strain range up to 0.095 and reduce relative error by 30-50%. This OCE method has the potential to become an effective tool in characterising mechanical properties of biological tissue.",

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AU - Wu, Hao

AU - Wang, Jiaqiu

AU - Catano, Jorge Alberto Amaya

AU - Sun, Cuiru

AU - Li, Zhiyong

PY - 2022/10/31

Y1 - 2022/10/31

N2 - A digital volume correlation (DVC)-based optical coherence elastography (OCE) method with inverse compositional Gauss-Newton (IC-GN) algorithm and second-order shape function is presented in this study. The systematic measurement errors of displacement and strain from our OCE method were less than 0.2 voxel and 4 × 10−4, respectively. Second-order shape function could better match complex deformation and decrease speckle rigidity-induced error. Compared to conventional methods, our OCE method could track a larger strain range up to 0.095 and reduce relative error by 30-50%. This OCE method has the potential to become an effective tool in characterising mechanical properties of biological tissue.

AB - A digital volume correlation (DVC)-based optical coherence elastography (OCE) method with inverse compositional Gauss-Newton (IC-GN) algorithm and second-order shape function is presented in this study. The systematic measurement errors of displacement and strain from our OCE method were less than 0.2 voxel and 4 × 10−4, respectively. Second-order shape function could better match complex deformation and decrease speckle rigidity-induced error. Compared to conventional methods, our OCE method could track a larger strain range up to 0.095 and reduce relative error by 30-50%. This OCE method has the potential to become an effective tool in characterising mechanical properties of biological tissue.

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Optical coherence elastography based on inverse compositional Gauss-Newton digital volume correlation with second-order shape function

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