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      Variability of Foveal Avascular Zone Metrics Derived From Optical Coherence Tomography Angiography Images

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          Abstract

          Purpose

          To characterize sources of inter- and intrasubject variability in quantitative foveal avascular zone (FAZ) metrics.

          Methods

          Two 3×3-mm optical coherence tomography angiography scans (centered on the fovea) were acquired in both eyes of 175 subjects. An image of the superficial plexus was extracted from each scan and segmented twice by a single observer. Four quantitative FAZ morphology metrics (area, axis ratio, acircularity, major horizontal axis angle) were calculated, and a variance components analysis was performed.

          Results

          Mean (±SD) age was 27.9 ± 11.9 years, and 55% were female. Area had the largest amount of variance resulting from intersubject differences (93.1%). In contrast, there was large interocular variance for axis ratio, acircularity, and major horizontal axis angle (55.0%, 53.7%, 70.7%, respectively), though only axis ratio showed significant asymmetry between fellow eyes ( P < 0.05). Neither repeated images from the same eye nor repeated segmentation on the same image were significant sources of variance.

          Conclusions

          Metrics of FAZ morphology show excellent repeatability and reliability. Excluding FAZ area, there was a high amount of variance attributed to interocular differences for the other FAZ metrics; therefore, the fellow eye should not be considered a control for FAZ studies when using these metrics.

          Translational Relevance

          Vision scientists must be prudent when choosing FAZ metrics, as they display varying degrees of within-subject differences relative to between-subject differences. It seems likely that different metrics will be best suited for different tasks, such as monitoring small changes over time within a single subject or assessing whether a given FAZ is abnormal.

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          Most cited references 61

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          NIH Image to ImageJ: 25 years of image analysis.

          For the past 25 years NIH Image and ImageJ software have been pioneers as open tools for the analysis of scientific images. We discuss the origins, challenges and solutions of these two programs, and how their history can serve to advise and inform other software projects.
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            ENLARGEMENT OF FOVEAL AVASCULAR ZONE IN DIABETIC EYES EVALUATED BY EN FACE OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY.

            To evaluate the area of the foveal avascular zone (FAZ) detected by en face OCTA (AngioVue, Avanti OCT; Optovue) in healthy and diabetic eyes.
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              • Record: found
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              Is Open Access

              Motion correction in optical coherence tomography volumes on a per A-scan basis using orthogonal scan patterns

              High speed Optical Coherence Tomography (OCT) has made it possible to rapidly capture densely sampled 3D volume data. One key application is the acquisition of high quality in vivo volumetric data sets of the human retina. Since the volume is acquired in a few seconds, eye movement during the scan process leads to distortion, which limits the accuracy of quantitative measurements using 3D OCT data. In this paper, we present a novel software based method to correct motion artifacts in OCT raster scans. Motion compensation is performed retrospectively using image registration algorithms on the OCT data sets themselves. Multiple, successively acquired volume scans with orthogonal fast scan directions are registered retrospectively in order to estimate and correct eye motion. Registration is performed by optimizing a large scale numerical problem as given by a global objective function using one dense displacement field for each input volume and special regularization based on the time structure of the acquisition process. After optimization, each volume is undistorted and a single merged volume is constructed that has superior signal quality compared to the input volumes. Experiments were performed using 3D OCT data from the macula and optic nerve head acquired with a high-speed ultra-high resolution 850 nm spectral OCT as well as wide field data acquired with a 1050 nm swept source OCT instrument. Evaluation of registration performance and result stability as well as visual inspection shows that the algorithm can correct for motion in all three dimensions and on a per A-scan basis. Corrected volumes do not show visible motion artifacts. In addition, merging multiple motion corrected and registered volumes leads to improved signal quality. These results demonstrate that motion correction and merging improves image quality and should also improve morphometric measurement accuracy from volumetric OCT data.
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                Author and article information

                Affiliations
                [1 ]Cell Biology, Neurobiology, & Anatomy, Medical College of Wisconsin, Milwaukee, WI, USA
                [2 ]National Institute for Health Research Biomedical Research Centre, Moorfields Eye Hospital and UCL Institute of Ophthalmology, London, UK
                [3 ]Ophthalmology & Visual Sciences, Medical College of Wisconsin, Milwaukee, WI, USA
                [4 ]School of Medicine, Medical College of Wisconsin, Milwaukee, WI, USA
                [5 ]Division of Biostatistics, Institute of Health and Equity, Medical College of Wisconsin, Milwaukee, WI, USA
                Author notes
                Correspondence: Joseph Carroll, Department of Ophthalmology & Visual Sciences, Medical College of Wisconsin, 925 N. 87th Street, Milwaukee, WI 53226-0509, USA; email: jcarroll@ 123456mcw.edu
                Journal
                Transl Vis Sci Technol
                Transl Vis Sci Technol
                tvst
                Transl Vis Sci Technol
                TVST
                Translational Vision Science & Technology
                The Association for Research in Vision and Ophthalmology
                2164-2591
                September 2018
                1 October 2018
                : 7
                : 5
                6166903 10.1167/tvst.7.5.20 tvst-07-05-07 TVST-18-0907
                Copyright 2018 The Authors

                This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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