Accuracy of retinal oximetry: a Monte Carlo investigation

Liu, Wenzhong; Jiao, Shuliang

doi:10.1117/1.jbo.18.6.066003

Cited by 33 publications

(55 citation statements)

References 49 publications

(80 reference statements)

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“…Anatomical variations in eye are reported among individuals, 29,30,34 which may affect measurement. To test the robustness of the RPE melanin quantification by PAOM, we varied the depth and diameter of the retinal blood vessel as well as the RPE thickness in the eye model.…”

Section: Influence Of Anatomical Variationsmentioning

confidence: 99%

“…The initial angle was randomly selected but will statistically follow a uniform distribution within the 2-deg field of view. 30,31 Most previous studies considered the posterior eye flat when the illumination angle was sufficiently small. In our study, however, the curvature of the fundus was also considered and a spherical coordinate was used.…”

Section: Monte Carlo Simulationmentioning

confidence: 99%

“…[30][31][32] In this study, our interest is the RPE, which is around 10 μm thick. In PAOM, optical absorption and scattering from neighboring layers, especially the highly optically absorbing choroid, will affect the detected PA signals from the RPE.…”

Section: Eye Modelmentioning

confidence: 99%

“…35 Except for the finer division of the choroid layer, our eye model is similar to what used in previous studies. [30][31][32]36 The wavelength-dependent optical absorption coefficients, scattering coefficients, and scattering anisotropy are extracted from the literatures 6,11,[31][32][33][36][37][38][39][40] and are summarized in Table 1. For the blood vessel, RPE, and the 3 choroid sublayers, we calculated the absorption coefficient based on hemoglobin (μ and E Q -T A R G E T ; t e m p : i n t r a l i n k -; e 0 0 2 ; 6 3 ;…”

mentioning

confidence: 99%

“…We placed a cylindrical blood vessel segment (diameter: 100 μm) 10-μm beneath the retina surface, 30 and the vessel wall thickness was set to be 10% of the vessel lumen diameter. 35 Except for the finer division of the choroid layer, our eye model is similar to what used in previous studies.…”

mentioning

confidence: 99%

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Monte Carlo investigation on quantifying the retinal pigment epithelium melanin concentration by photoacoustic ophthalmoscopy

2015

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Abstract. The retinal pigment epithelium (RPE) melanin plays an important role in maintaining normal visual functions. A decrease in the RPE melanin concentration with aging is believed to be associated with several blinding diseases, including age-related macular degeneration. Quantifying the RPE melanin noninvasively is therefore important in evaluating the retinal health and aging conditions. Photoacoustic ophthalmoscopy (PAOM), as an optical absorption-based imaging technology, can potentially be applied to measure variations in the RPE melanin if the relationship between the detected photoacoustic (PA) signal amplitudes and the RPE melanin concentrations can be established. In this work, we tested the feasibility of using PA signals from retinal blood vessels as references to measure RPE melanin variation using Monte Carlo (MC) simulation. The influences from PAOM axial resolution, the depth and diameter of the retinal blood vessel, and the RPE thickness were examined. We proposed a calibration scheme by relating detected PA signals to the RPE melanin concentrations, and we found that the scheme is robust to these tested parameters. This study suggests that PAOM has the capability of quantitatively measuring the RPE melanin in vivo.

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Section: Influence Of Anatomical Variationsmentioning

confidence: 99%

Section: Monte Carlo Simulationmentioning

confidence: 99%

Section: Eye Modelmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Monte Carlo investigation on quantifying the retinal pigment epithelium melanin concentration by photoacoustic ophthalmoscopy

2015

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Snapshot hyperspectral retinal imaging using compact spectral resolving detector array

Liu

Dong

et al. 2016

Journal of Biophotonics

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Hyperspectral retinal imaging captures the light spectrum from each imaging pixel. It provides spectrally encoded retinal physiological and morphological information, which could potentially benefit diagnosis and therapeutic monitoring of retinal diseases. The key challenges in hyperspectral retinal imaging are how to achieve snapshot imaging to avoid motions between the images from multiple spectral bands, and how to design a compact snapshot imager suitable for clinical use. Here, we developed a compact, snapshot hyperspectral fundus camera for rodents using a novel spectral resolving detector array (SRDA), on which a thin-film Fabry–Perot cavity filter was monolithically fabricated on each imaging pixel. We achieved hyperspectral retinal imaging with 16 wavelength bands (460 to 630 nm) at 20 fps. We also demonstrated false-color vessel contrast enhancement and retinal oxygen saturation (sO2) measurement through spectral analysis. This work could potentially bring hyperspectral retinal imaging from bench to bedside.

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In vivo blind‐deconvolution photoacoustic ophthalmoscopy with total variation regularization

Xie

Gao

et al. 2018

Journal of Biophotonics

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Photoacoustic ophthalmoscopy (PAOM) is capable of noninvasively imaging anatomic and functional information of the retina in living rodents. However, the strong ocular aberration in rodent eyes and limited ultrasonic detection sensitivity affect PAOM's spatial resolution and signal-to-noise ratio (SNR) in in vivo eyes. In this work, we report a computational approach to combine blind deconvolution (BD) algorithm with a regularizing constraint based on total variation (BDTV) for PAOM imaging restoration. We tested the algorithm in retinal and choroidal microvascular images in albino rat eyes. The algorithm improved PAOM's lateral resolution by around 2-fold. Moreover, it enabled the improvement in imaging SNR for both major vessels and capillaries, and realized the well-preserved blood vessels' edges simultaneously, which surpasses conventional Richardson-Lucy BD algorithm. The reported results indicate that the BDTV algorithm potentially facilitate PAOM in extracting retinal pathophysiological information by enhancing in vivo imaging quality without physically modifying PAOM's optical configuration.

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Accuracy of retinal oximetry: a Monte Carlo investigation

Cited by 33 publications

References 49 publications

Monte Carlo investigation on quantifying the retinal pigment epithelium melanin concentration by photoacoustic ophthalmoscopy

Monte Carlo investigation on quantifying the retinal pigment epithelium melanin concentration by photoacoustic ophthalmoscopy

Snapshot hyperspectral retinal imaging using compact spectral resolving detector array

In vivo blind‐deconvolution photoacoustic ophthalmoscopy with total variation regularization

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