Paper
21 February 2019 Simultaneous reconstruction and displacement estimation for spectral-domain optical coherence elastography
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Abstract
Optical coherence elastography allows the characterization of the mechanical properties of tissues, and can be performed through estimating local displacement maps from subsequent acquisitions of a sample under different loads. This displacement estimation is limited by noise in the images, which can be high in dynamic systems due to the inability to perform long exposures or B-scan averaging. In this work, we propose a framework for simultaneously enhancing both the image quality and displacement map for elastography, by motion compensated denoising with the block-matching and 4D filtering (BM4D) method, followed by a re-estimation of displacement. We adopt the interferometric synthetic aperture microscopy (ISAM) method to enhance the lateral resolution away from the focal plane, and use sub-pixel cross correlation block matching for non-uniform deformation estimation. We validate this approach on data from a commercial spectral domain optical coherence tomography system, whereby we observe an enhancement of both image and displacement accuracy of up to 33% over a standard approach.
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jonathan H. Mason, Yvonne Reinwald, Ying Yang, Sarah Waters, Alicia El Haj, and Pierre O. Bagnaninchi "Simultaneous reconstruction and displacement estimation for spectral-domain optical coherence elastography", Proc. SPIE 10880, Optical Elastography and Tissue Biomechanics VI, 108801K (21 February 2019); https://doi.org/10.1117/12.2508326
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Cited by 1 scholarly publication.
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KEYWORDS
Denoising

Elastography

Motion estimation

Coherence (optics)

Optical coherence tomography

Image enhancement

Image quality

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