Retinal Oximetry With a Scanning Laser Ophthalmoscope

Kristjánsdóttir, Jóna Valgerður; Hardarson, Sveinn Hákon; Halldorsson, Gisli H.; Karlsson, Robert Arnar; Eliasdottir, Thorunn Scheving; Stefánsson, Einar

doi:10.1167/iovs.13-13255

Cited by 27 publications

(34 citation statements)

References 20 publications

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“…As the optical absorption coefficient of whole blood is the linear combination of these two forms of hemoglobin, multi-wavelength spectroscopy can be used to retrieve relative HbO 2 -HbR concentration ratio and thus sO 2 . Fundus photography [4][5][6][7], scanning laser ophthalmoscopy [19], and hyperspectral imaging [20,21] have all been investigated to measure retinal circulation sO 2 in humans. These approaches rely on the backscattered photons from blood vessels and share similar imaging principle.…”

Section: Introductionmentioning

confidence: 99%

Retinal oximetry in humans using visible-light optical coherence tomography [Invited]

Chen

Xiao

Nesper

et al. 2017

Biomed. Opt. Express

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Abstract:We measured hemoglobin oxygen saturation (sO 2 ) in the retinal circulation in healthy humans using visible-light optical coherence tomography (vis-OCT). The measurements showed clear oxygenation differences between central retinal arteries and veins close to the optic nerve head. Spatial variations at different vascular branching levels were also revealed. In addition, we presented theoretical and experimental results to establish that noises in OCT intensity followed Rice distribution. We used this knowledge to retrieve unbiased estimation of true OCT intensity to improve the accuracy of vis-OCT oximetry, which had inherently lower signal-to-nose ratio from human eyes due to safety and comfort limitations. We demonstrated that the new statistical-fitting sampling strategy could reduce the estimation error in sO 2 by three percentage points (pp). The presented work aims to provide a foundation for using vis-OCT to achieve accurate retinal oximetry in clinical settings. G. Garhöfer, and L. Schmetterer, "Retinal oxygen metabolism during normoxia and hyperoxia in healthy subjects," Invest.

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Section: Introductionmentioning

confidence: 99%

Retinal oximetry in humans using visible-light optical coherence tomography [Invited]

Chen

Xiao

Nesper

et al. 2017

Biomed. Opt. Express

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“…Adding new wavelengths will make the system achieve multi-spectral imaging. Multi-spectral retinal imaging has gained interest in recent years [30,31] as it helps gathering quantitative information on retinal health.…”

Section: Discussionmentioning

confidence: 99%

Digital micromirror device based ophthalmoscope with concentric circle scanning

Damodaran

Vienola

Braaf

et al. 2017

Biomed. Opt. Express

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Abstract:Retinal imaging is demonstrated using a novel scanning light ophthalmoscope based on a digital micromirror device with 810 nm illumination. Concentric circles were used as scan patterns, which facilitated fixation by a human subject for imaging. An annular illumination was implemented in the system to reduce the background caused by corneal reflections and thereby to enhance the signal-to-noise ratio. A 1.9-fold increase in the signal-to-noise ratio was found by using an annular illumination aperture compared to a circular illumination aperture, resulting in a 5-fold increase in imaging speed and a better signal-to-noise ratio compared to our previous system. We tested the imaging performance of our system by performing nonmydriatic imaging on two subjects at a speed of 7 Hz with a maximum 20 • (diameter) field of view. The images were shot noise limited and clearly show various anatomical features of the retina with high contrast.

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“…After model test and uncertainty analysis, we used the testing data from Ref. [12] and applied the FNN and CNN models for retinal imaging oximetry in comparison to LSF (Fig. 6), at three different ventilation conditions.…”

Section: En Face So2 Maps With Uncertainty Quantificationmentioning

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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Retinal Oximetry With a Scanning Laser Ophthalmoscope

Cited by 27 publications

References 20 publications

Retinal oximetry in humans using visible-light optical coherence tomography [Invited]

Retinal oximetry in humans using visible-light optical coherence tomography [Invited]

Digital micromirror device based ophthalmoscope with concentric circle scanning

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

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