Visible-light optical coherence tomography: a review

Xiao, Shuangjiu; Beckmann, Lisa; Zhang, Hao F.

doi:10.1117/1.jbo.22.12.121707

Cited by 144 publications

(111 citation statements)

References 94 publications

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“…Vis-OCT is a newly developed OCT technology, which uses visible light as its light source rather than the commonly used near-infrared light in commercial OCT systems. [28][29][30] Using shorter wavelengths allows for higher axial resolution for a given bandwidth and higher backscattering sensitivity in tissue. 31,32 The higher axial resolution allows more precise measurement of SC anatomy as well as SC changes.…”

mentioning

confidence: 99%

In Vivo Imaging of Schlemm's Canal and Limbal Vascular Network in Mouse Using Visible-Light OCT

Zhou

Beckmann

Miller

et al. 2020

Invest. Ophthalmol. Vis. Sci.

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PURPOSE.To validate the ability of visible-light optical coherence tomography (vis-OCT) in imaging the full Schlemm's canal (SC) and its surrounding limbal vascular network in mice in vivo through a compound circumlimbal scan. METHODS.We developed an anterior segment vis-OCT system and a compound circumlimbal scanning method, which montages eight rotated raster scans. We calibrated the circumlimbal scan geometry using a three-dimensional printed phantom eyeball before imaging wild-type C57BL/6J mice. We measured SC size by segmenting SC cross sections from vis-OCT B-scan images and imaged the limbal microvascular network using vis-OCT angiography (vis-OCTA). To introduce changes in SC size, we used a manometer to adjust the intraocular pressure (IOP) to different levels. To create additional optical scattering contrast to enhance SC imaging, we surgically increased the episcleral venous pressure (EVP) and caused blood reflux into SC. RESULTS.Using the compound circumlimbal scan, our anterior segment vis-OCT noninvasively imaged the full SC and limbal microvascular network in mouse for the first time. We observed an average 123% increase in SC volume when we decreased the IOP by 10 mm Hg from the baseline IOP of 7 to 10 mm Hg and an average 72% decrease in SC volume when the IOP level was elevated by 10 mm Hg from the baseline IOP. We also observed location-dependent SC size responses to IOP changes. Blood reflux caused by increased EVP enabled vis-OCTA to directly visualize SC, which matched well with the segmented SC. CONCLUSIONS.Vis-OCT and vis-OCTA can accurately image the entire SC and limbal microvascular network in vivo using the compound circumlimbal scan. Vis-OCT is also able to quantitatively measure SC responses to changing IOP levels.

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confidence: 99%

In Vivo Imaging of Schlemm's Canal and Limbal Vascular Network in Mouse Using Visible-Light OCT

Zhou

Beckmann

Miller

et al. 2020

Invest. Ophthalmol. Vis. Sci.

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“…Moreover, working with large spectral bands increases the risk of optical dispersion mismatch between the sample and the reference arms, and may inevitably deteriorate the resolution in depth. Working at shorter wavelengths between 500 and 700 nm, as certain visible-light OCT [31], may be a better option. A silicon-based camera could be used instead of an expensive InGaAs camera.…”

Section: Resultsmentioning

confidence: 99%

Simultaneous dual-band line-field confocal optical coherence tomography: application to skin imaging

Davis¹,

Levecq²,

Azimani³

et al. 2019

Biomed. Opt. Express

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“…However, in practice these two parameters cannot fully capture all the experimental variabilities. While other models may reduce the free parameters to avoid overfitting [14,17,19,[23][24][25], this approach in general is nonetheless rigid and over-simplified to the actual experiments.…”

Section: Principle Of Least Square Fittingmentioning

confidence: 99%

Deep spectral learning for label-free optical imaging oximetry with uncertainty quantification

Liu¹,

Cheng

Tian

et al. 2019

Preprint

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Measurement of blood oxygen saturation (sO2) by optical imaging oximetry provides invaluable insight into local tissue functions and metabolism. Despite different embodiments and modalities, all label-free optical imaging oximetry utilize the same principle of sO2-dependent spectral contrast from hemoglobin. Traditional approaches for quantifying sO2 often rely on analytical models that are fitted by the spectral measurements. These approaches in practice suffer from uncertainties due to biological variability, tissue geometry, light scattering, systemic spectral bias, and variations in experimental conditions. Here, we propose a new data-driven approach, termed deep spectral learning (DSL) for oximetry to be highly robust to experimental variations, and more importantly to provide uncertainty quantification for each sO2 prediction. To demonstrate the robustness and generalizability of DSL, we analyze data from two visible light optical coherence tomography (vis-OCT) setups across two separate in vivo experiments in rat retina. Predictions made by DSL are highly adaptive to experimental variabilities as well as the depth-dependent backscattering spectra. Two neural-network-based models are tested and compared with the traditional least-squares fitting (LSF) method. The DSL-predicted sO2 shows significantly lower mean-square errors than the LSF. For the first time, we have demonstrated en face maps of retinal oximetry along with pixel-wise confidence assessment. Our DSL overcomes several limitations in the traditional approaches and provides a more flexible, robust, and reliable deep learning approach for in vivo non-invasive label-free optical oximetry.

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Visible-light optical coherence tomography: a review

Cited by 144 publications

References 94 publications

In Vivo Imaging of Schlemm's Canal and Limbal Vascular Network in Mouse Using Visible-Light OCT

In Vivo Imaging of Schlemm's Canal and Limbal Vascular Network in Mouse Using Visible-Light OCT

Simultaneous dual-band line-field confocal optical coherence tomography: application to skin imaging

Deep spectral learning for label-free optical imaging oximetry with uncertainty quantification

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