Convolutional dictionary learning for blind deconvolution of optical coherence tomography images

Wang, Junzhe; Wohlberg, Brendt; Adamson, R. B. A.

doi:10.1364/BOE.447394

Convolutional dictionary learning for blind deconvolution of optical coherence tomography images

Journal Article · Thu Mar 03 00:00:00 EST 2022 · Biomedical Optics Express

DOI:https://doi.org/10.1364/BOE.447394· OSTI ID:1847176

; Wohlberg, Brendt; Adamson, R. B. A.

In this study, we demonstrate a sparsity-regularized, complex, blind deconvolution method for removing sidelobe artefacts and stochastic noise from optical coherence tomography (OCT) images. Our method estimates the complex scattering amplitude of tissue on a line-by-line basis by estimating and deconvolving the complex, one-dimensional axial point spread function (PSF) from measured OCT A-line data. We also present a strategy for employing a sparsity weighting mask to mitigate the loss of speckle brightness within tissue-containing regions caused by the sparse deconvolution. Qualitative and quantitative analyses show that this approach suppresses sidelobe artefacts and background noise better than traditional spectral reshaping techniques, with negligible loss of tissue structure. The technique is particularly useful for emerging OCT applications where OCT images contain strong specular reflections at air-tissue boundaries that create large sidelobe artefacts.

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Sponsoring Organization:: USDOE

OSTI ID:: 1847176

Alternate ID(s):: OSTI ID: 1883151

Journal Information:: Biomedical Optics Express, Journal Name: Biomedical Optics Express Journal Issue: 4 Vol. 13; ISSN 2156-7085

Publisher:: Optical Society of AmericaCopyright Statement

Country of Publication:: United States

Language:: English

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