Highly sensitive and robust strain retrieval in optical coherence elastography

Balazs Dura-Kovacs; Andrea Mazzolani; Jakub Zalesak; Jiayue Li; Matt S. Hepburn; Brendan F. Kennedy; Peter R. T. Munro

doi:10.1117/12.2649798

9 March 2023 Highly sensitive and robust strain retrieval in optical coherence elastography

Balazs Dura-Kovacs, Andrea Mazzolani, Jakub Zalesak, Jiayue Li, Matt S. Hepburn, Brendan F. Kennedy, Peter R. T. Munro

Proceedings Volume PC12367, Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XXVII; PC1236717 (2023) https://doi.org/10.1117/12.2649798
Event: SPIE BiOS, 2023, San Francisco, California, United States

Abstract

Strain retrieval from maps of displacement due to mechanical loading is central to optical coherence elsatography. However, displacement data is usually highly oscillatory since it is derived from the phase difference between OCT images. Oscillations limit sensitivity and signal to noise ratio of retrieved strain. We present an alternative approach to strain retrieval that does not use phase difference, but determines the unique spectral domain transformation that maps the unloaded A-scan to the loaded A-scan, exactly, for regions of constant strain. Our novel method of strain retrieval has a higher sensitivity and signal to noise ratio than existing approaches.

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Citation Download Citation

Balazs Dura-Kovacs, Andrea Mazzolani, Jakub Zalesak, Jiayue Li, Matt S. Hepburn, Brendan F. Kennedy, and Peter R. T. Munro "Highly sensitive and robust strain retrieval in optical coherence elastography", Proc. SPIE PC12367, Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XXVII, PC1236717 (9 March 2023); https://doi.org/10.1117/12.2649798

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KEYWORDS

Tissue optics

Coherence (optics)

Elastography

Optical coherence tomography

Speckle pattern

Tissues

Signal to noise ratio

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