2013
DOI: 10.1364/josaa.30.002595
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Automated segmentation of retinal pigment epithelium cells in fluorescence adaptive optics images

Abstract: Adaptive optics (AO) imaging methods allow the histological characteristics of retinal cell mosaics, such as photoreceptors and retinal pigment epithelium (RPE) cells, to be studied in vivo. The high-resolution images obtained with ophthalmic AO imaging devices are rich with information that is difficult and/or tedious to quantify using manual methods. Thus, robust, automated analysis tools that can provide reproducible quantitative information about the cellular mosaics under examination are required. Automat… Show more

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Cited by 22 publications
(16 citation statements)
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“…Semiautomated custom segmentation software 44 and photoreceptor marking software (based on a previously published algorithm 45 ) produced binary images of RPE cell boundaries and photoreceptor coordinates for each ROI. Automated RPE segmentation errors were manually corrected as previously described, 22 where segmentation within ROIs was limited to cell boundaries that could be discerned confidently by a grader.…”
Section: Methodsmentioning
confidence: 99%
“…Semiautomated custom segmentation software 44 and photoreceptor marking software (based on a previously published algorithm 45 ) produced binary images of RPE cell boundaries and photoreceptor coordinates for each ROI. Automated RPE segmentation errors were manually corrected as previously described, 22 where segmentation within ROIs was limited to cell boundaries that could be discerned confidently by a grader.…”
Section: Methodsmentioning
confidence: 99%
“…An early version of a cell segmentation algorithm [38], developed in-house and implemented in MATLAB (MathWorks, Natick, MA, USA), was used to extract the boundaries of individual RPE cells. Briefly, the algorithm used several image processing steps, including smoothing, edge detection, edge correction and binarization to produce a binary image of the borders of RPE cells.…”
Section: Rpe Cell Segmentation and Analysismentioning
confidence: 99%
“…Deployment of adaptive optics (AO) in fundus cameras, 14 cSLO, 15 and OCT 16 instruments has further improved optical resolution, thus permitting imaging of single cells, such as rods, foveal cones, 17 , 18 RPE cells, 19 and blood cells in small retinal vessels. 20 , 21 This is of interest for monitoring longitudinal changes in diseases, such as retinitis pigmentosa, 22 , 23 retinal dystrophy, 24 26 age-related macular degeneration, 27 , 28 and diabetic retinopathies, 29 31 especially since cellular scale imaging can permit semiautomated quantification of the density and spacing of these cells 32 – 37 as well as AO-assisted microperimetry, 38 , 39 …”
mentioning
confidence: 99%