Quantitative Thickness Measurement of Retinal Layers Imaged by Optical Coherence Tomography

Shahidi, Mahnaz; Wang, Zhangwei; Zelkha, Ruth

doi:10.1016/j.ajo.2005.01.012

Cited by 111 publications

(78 citation statements)

References 16 publications

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“…Over the past two decades, the application of image processing and computer vision to OCT image interpretation has mostly focused on the development of automated retinal layer segmentation methods [4][5][6][7][8][9][10][11][12][13][14][15][16][17][18]. Segmented layer thicknesses are compared to the corresponding thickness measurements from normative databases to help identify retinal diseases [19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Fully automated detection of diabetic macular edema and dry age-related macular degeneration from optical coherence tomography images

Srinivasan¹,

Kim²,

Mettu³

et al. 2014

Biomed. Opt. Express

411

302

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Abstract:We present a novel fully automated algorithm for the detection of retinal diseases via optical coherence tomography (OCT) imaging. Our algorithm utilizes multiscale histograms of oriented gradient descriptors as feature vectors of a support vector machine based classifier. The spectral domain OCT data sets used for cross-validation consisted of volumetric scans acquired from 45 subjects: 15 normal subjects, 15 patients with dry age-related macular degeneration (AMD), and 15 patients with diabetic macular edema (DME). Our classifier correctly identified 100% of cases with AMD, 100% cases with DME, and 86.67% cases of normal subjects. This algorithm is a potentially impactful tool for the remote diagnosis of ophthalmic diseases.

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Section: Introductionmentioning

confidence: 99%

Fully automated detection of diabetic macular edema and dry age-related macular degeneration from optical coherence tomography images

Srinivasan¹,

Kim²,

Mettu³

et al. 2014

Biomed. Opt. Express

411

302

View full text Add to dashboard Cite

show abstract

“…This limitation in the Stratus OCT system has stimulated interest in developing segmentation algorithms to better detect the local changes in the retinal structure. [3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18] In addition, the quantification provided by this system is often imprecise because of erroneous detection of the inner and outer borders of the retina. [19][20][21] As a result, potentially useful quantitative information is not extracted by the current commercial Stratus OCT.…”

Section: Introductionmentioning

confidence: 99%

Improving image segmentation performance and quantitative analysis via a computer-aided grading methodology for optical coherence tomography retinal image analysis

et al. 2010

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Abstract. We demonstrate quantitative analysis and error correction of optical coherence tomography ͑OCT͒ retinal images by using a custom-built, computer-aided grading methodology. A total of 60 Stratus OCT ͑Carl Zeiss Meditec, Dublin, California͒ B-scans collected from ten normal healthy eyes are analyzed by two independent graders. The average retinal thickness per macular region is compared with the automated Stratus OCT results. Intergrader and intragrader reproducibility is calculated by Bland-Altman plots of the mean difference between both gradings and by Pearson correlation coefficients. In addition, the correlation between Stratus OCT and our methodology-derived thickness is also presented. The mean thickness difference between Stratus OCT and our methodology is 6.53 m and 26.71 m when using the inner segment/outer segment ͑IS/OS͒ junction and outer segment/retinal pigment epithelium ͑OS/RPE͒ junction as the outer retinal border, respectively. Overall, the median of the thickness differences as a percentage of the mean thickness is less than 1% and 2% for the intragrader and intergrader reproducibility test, respectively. The measurement accuracy range of the OCT retinal image analysis ͑OCTRIMA͒ algorithm is between 0.27 and 1.47 m and 0.6 and 1.76 m for the intragrader and intergrader reproducibility tests, respectively. Pearson correlation coefficients demonstrate R 2 Ͼ 0.98 for all Early Treatment Diabetic Retinopathy Study ͑ETDRS͒ regions. Our methodology facilitates a more robust and localized quantification of the retinal structure in normal healthy controls and patients with clinically significant intraretinal features.

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“…22 Since the nasal Henle's fibre layer is thicker in this OCT measurement and also appears to be thicker histologically, 23 we propose that the GDx measurements from the left eyes demonstrate a greater retardance because of this asymmetry in the thickness of the Henle fibre layer. Our GDx retardance measurements were 13% greater in left eyes than right.…”

Section: Eyementioning

confidence: 74%

Accuracy of GDx variable corneal compensation polarization measurements in normal human eyes: effect of accommodation, cycloplegia, focus, pupil size, and eye selection on reproducibility

Levy¹,

Schachar²

2005

Eye

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Accuracy of GDx variable corneal compensation polarization measurements in normal human eyes: effect of accommodation, cycloplegia, focus, pupil size, and eye selection on reproducibility NS Levy and IH Schachar AbstractPurpose To evaluate the reproducibility of variable corneal compensation (VCC) and the effect of accommodation, cycloplegia, eye selection, focus, and pupil size on this measurement of polarization. Methods Using a GDx scanning laser polarimeter, multiple measurements of the VCC were obtained from each eye of 33 healthy, young adults under differing conditions. Pupil size and refraction were independently measured with a pupillometer and an autorefractometer. The effects of eye, instrument focus, pupil diameter, cycloplegia, and accommodation were statistically assessed.Results The reproducibility of a single retardation measurement and its axis, as determined by the standard deviations (SD) of repeated measurements, is 71.58 nm and 2.101, respectively. There is a difference in retardation between right and left eyes, of 5.2679 nm, P ¼ 0.002. Increasing pupil size increases retardation. Cycloplegia or defocusing decreases retardation, and pharmacologically induced accommodation has no effect on retardation. Conclusions The retardation and its axis are highly reproducible measurements when the pupil is of physiologic size and the GDx is properly focused. There is a consistent difference in VCC retardation between the paired right and left eyes. This difference may reflect equipment-induced measurement artefact and/or an anatomic asymmetry between the paired eyes of the subjects studied. Clinicians should be cautious when comparing interocular VCC measurements between paired right and left eyes and using data pooled from both eyes for age-adjusted, normalized standards.

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Quantitative Thickness Measurement of Retinal Layers Imaged by Optical Coherence Tomography

Cited by 111 publications

References 16 publications

Fully automated detection of diabetic macular edema and dry age-related macular degeneration from optical coherence tomography images

Fully automated detection of diabetic macular edema and dry age-related macular degeneration from optical coherence tomography images

Improving image segmentation performance and quantitative analysis via a computer-aided grading methodology for optical coherence tomography retinal image analysis

Accuracy of GDx variable corneal compensation polarization measurements in normal human eyes: effect of accommodation, cycloplegia, focus, pupil size, and eye selection on reproducibility

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