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    1. An Artificial Intelligence Approach to Assess Spatial Patterns of Retinal Nerve Fiber Layer Thickness Maps in Glaucoma

      An Artificial Intelligence Approach to Assess Spatial Patterns of Retinal Nerve Fiber Layer Thickness Maps in Glaucoma

      Purpose : The purpose of this study was to classify the spatial patterns of retinal nerve fiber layer thickness (RNFLT) and assess their associations with visual field (VF) loss in glaucoma. Methods : We used paired reliable 24-2 VFs and optical coherence tomography scans of 691 eyes from 691 patients. The RNFLT maps were used to determine the RNFLT patterns (RPs) by non-negative matrix factorization (NMF). The RPs were correlated with mean deviation (MD), spherical equivalent (SE), and major blood vessel locations. The RPs were further used to predict the 52 total deviation (TD) values by linear regression compared with models using ...

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    2. Quantitative Optical Coherence Tomography Angiography Parameters in Type 1 Macular Neovascularization Secondary to Age-Related Macular Degeneration

      Quantitative Optical Coherence Tomography Angiography Parameters in Type 1 Macular Neovascularization Secondary to Age-Related Macular Degeneration

      Purpose : The purpose of this paper was to study type 1 macular neovascularization (MNV) quantitative optical coherence tomography (OCT) angiography (OCTA) features by means of advanced postprocessing analyses. Methods : We recruited patients affected by naïve type 1 MNV secondary to age-related macular degeneration (AMD) and age-matched controls. All patients underwent ophthalmologic examination and multimodal imaging. They were treated with pro-re-nata anti-VEGF injections. The ensuing follow-up lasted 24 months. Quantitative OCT and OCTA parameters were statistically analyzed to obtain cutoff values able to distinguish two clinically different patient subgroups. Main outcome measures were best-corrected visual acuity (BCVA), central macular thickness ...

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    3. Intradevice Repeatability and Interdevice Agreement of Ocular Biometric Measurements: A Comparison of Two Swept-Source Anterior Segment OCT Devices

      Intradevice Repeatability and Interdevice Agreement of Ocular Biometric Measurements: A Comparison of Two Swept-Source Anterior Segment OCT Devices

      Purpose : To assess the repeatability and agreement of ocular biometric parameters measured using the Tomey CASIA SS-1000 and Heidelberg ANTERION anterior segment optical coherence tomography (AS-OCT) devices. Methods : Both eyes of subjects 18 years of age or older were scanned three times with the CASIA and ANTERION under standardized dark lighting. One AS-OCT image along the horizontal (temporal-nasal) meridian was analyzed per eye and per scan. Pupillary diameter (PD) was within 15% for all pairwise comparisons. Anterior chamber depth, lens vault, anterior chamber width, angle opening distance, trabecular iris space area, and scleral spur angle (SSA500) were measured using manufacturer-provided ...

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    4. An Intelligent Optical Coherence Tomography-based System for Pathological Retinal Cases Identification and Urgent Referrals

      An Intelligent Optical Coherence Tomography-based System for Pathological Retinal Cases Identification and Urgent Referrals

      Purpose : This study aimed to develop an automated system with artificial intelligence algorithms to comprehensively identify pathologic retinal cases and make urgent referrals. Methods : To build and test the intelligent system, this study obtained 28,664 optical coherence tomography (OCT) images from 2254 patients in the Eye and ENT Hospital of Fudan University (EENT Hospital) and Shanghai Tenth People's Hospital (TENTH Hospital). We applied a deep learning model with an adapted feature pyramid network to detect 15 categories of retinal pathologies from OCT images as common signs of various retinal diseases. Subsequently, the pathologies detected in the OCT images ...

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    5. Transfer Learning for Automated OCTA Detection of Diabetic Retinopathy

      Transfer Learning for Automated OCTA Detection of Diabetic Retinopathy

      Purpose : To test the feasibility of using deep learning for optical coherence tomography angiography (OCTA) detection of diabetic retinopathy. Methods : A deep-learning convolutional neural network (CNN) architecture, VGG16, was employed for this study. A transfer learning process was implemented to retrain the CNN for robust OCTA classification. One dataset, consisting of images of 32 healthy eyes, 75 eyes with diabetic retinopathy (DR), and 24 eyes with diabetes but no DR (NoDR), was used for training and cross-validation. A second dataset consisting of 20 NoDR and 26 DR eyes was used for external validation. To demonstrate the feasibility of using artificial ...

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    6. A Review of Deep Learning for Screening, Diagnosis, and Detection of Glaucoma Progression

      A Review of Deep Learning for Screening, Diagnosis, and Detection of Glaucoma Progression

      Because of recent advances in computing technology and the availability of large datasets, deep learning has risen to the forefront of artificial intelligence, with performances that often equal, or sometimes even exceed, those of human subjects on a variety of tasks, especially those related to image classification and pattern recognition. As one of the medical fields that is highly dependent on ancillary imaging tests, ophthalmology has been in a prime position to witness the application of deep learning algorithms that can help analyze the vast amount of data coming from those tests. In particular, glaucoma stands as one of the ...

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    7. Using the Pathophysiology of Dry AMD to Guide Binarization of the Choriocapillaris on OCTA: A Model

      Using the Pathophysiology of Dry AMD to Guide Binarization of the Choriocapillaris on OCTA: A Model

      Especially since the incorporation of swept laser sources, optical coherence tomography angiography (OCTA) has enabled quantification of choriocapillaris perfusion. A critical step in this process is binarization, which makes angiographic images quantifiable in terms of perfusion metrics. It remains challenging to have confidence that choriocapillaris perfusion metrics reflect the reality of pathophysiologic flow, largely because choice of binarization method can result in significantly different perfusion metric outcomes. This commentary discusses a proof-of-concept case involving comparative assessment of binarization methods for a set of dry age-related macular degeneration OCTA data. One of these methods was deemed preferable based on superior agreement ...

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    8. Comparison of SDOCT Scan Types for Grading Disorganization of Retinal Inner Layers and Other Morphologic Features of Diabetic Macular Edema

      Comparison of SDOCT Scan Types for Grading Disorganization of Retinal Inner Layers and Other Morphologic Features of Diabetic Macular Edema

      Purpose : To assess grading reproducibility of disorganization of the retinal inner layers (DRIL) and other morphologic features of diabetic macular edema (DME) across spectral domain optical coherence tomography (SDOCT) instruments and scan types. Methods : A cross-sectional study enrolled participants with current or recent center-involved DME. In group A (27 eyes), we obtained two Cirrus scans (512 × 128 macular cube [Cube] and high-definition five-line raster [HD 5-Line]) and two Spectralis scans (high-resolution [HR] and high-speed [HS]). In group B, 26 eyes underwent HR scans and Optovue AngioVue (OP) 3 × 3-mm scans. All scans were graded for type and extent of DRIL ...

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    9. Application of a Deep Machine Learning Model for Automatic Measurement of EZ Width in SD-OCT Images of RP

      Application of a Deep Machine Learning Model for Automatic Measurement of EZ Width in SD-OCT Images of RP

      Purpose : We applied a deep convolutional neural network model for automatic identification of ellipsoid zone (EZ) in spectral domain optical coherence tomography B-scans of retinitis pigmentosa (RP). Methods : Midline B-scans having visible EZ from 220 patients with RP and 20 normal subjects were manually segmented for inner limiting membrane, inner nuclear layer, EZ, retinal pigment epithelium, and Bruch's membrane. A total of 2.87 million labeled image patches (33 × 33 pixels) extracted from 480 B-scans were used for training a convolutional neural network model implemented in MATLAB. B-scans from a separate group of 80 patients with RP were used ...

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    10. Deep Neural Network for Scleral Spur Detection in Anterior Segment OCT Images: The Chinese American Eye Study

      Deep Neural Network for Scleral Spur Detection in Anterior Segment OCT Images: The Chinese American Eye Study

      Purpose : To develop a deep neural network that detects the scleral spur in anterior segment optical coherence tomography (AS-OCT) images. Methods : Participants in the Chinese American Eye Study, a population-based study in Los Angeles, California, underwent complete ocular examinations, including AS-OCT imaging with the Tomey CASIA SS-1000. One human expert grader provided reference labels of scleral spur locations in all images. A convolutional neural network (CNN)-based on the ResNet-18 architecture was developed to detect the scleral spur in each image. Performance of the CNN model was assessed by calculating prediction errors, defined as the difference between the Cartesian coordinates ...

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    11. Ensemble Deep Learning for Diabetic Retinopathy Detection Using Optical Coherence Tomography Angiography

      Ensemble Deep Learning for Diabetic Retinopathy Detection Using Optical Coherence Tomography Angiography

      Purpose : To evaluate the role of ensemble learning techniques with deep learning in classifying diabetic retinopathy (DR) in optical coherence tomography angiography (OCTA) images and their corresponding co-registered structural images. Methods : A total of 463 volumes from 380 eyes were acquired using the 3 × 3-mm OCTA protocol on the Zeiss Plex Elite system. Enface images of the superficial and deep capillary plexus were exported from both the optical coherence tomography and OCTA data. Component neural networks were constructed using single data-types and fine-tuned using VGG19, ResNet50, and DenseNet architectures pretrained on ImageNet weights. These networks were then ensembled using majority ...

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    12. Characterization of the Three Distinct Retinal Capillary Plexuses Using Optical Coherence Tomography Angiography in Myopic Eyes

      Characterization of the Three Distinct Retinal Capillary Plexuses Using Optical Coherence Tomography Angiography in Myopic Eyes

      Purpose : To segment and quantify three distinct retinal capillary plexuses using optical coherence tomography angiography (OCTA) in myopic eyes. Methods : We analyzed 96 eyes from 62 subjects with myopia (27.76 ± 7.05 years of age) and evaluated 30 normal eyes from 15 subjects (28.33 ± 3.13 years of age) for controls. En face OCTA images generated by AngioPlex (Carl Zeiss; Oberkochen, Germany) were manually segmented by the progressive matching method into superficial, middle, and deep capillary plexuses (SCPs, MCPs, and DCPs, respectively). Estimated positions for each plexus relative to the reference line were calculated. After strict artifact removal ...

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    13. Subretinal Fibrosis Detection Using Polarization Sensitive Optical Coherence Tomography

      Subretinal Fibrosis Detection Using Polarization Sensitive Optical Coherence Tomography

      Purpose : Subretinal fibrosis (SRFib) is an important cause of permanent loss-of-vision diseases with submacular neovascularization, but a reliable diagnostic method is currently missing. This study uses polarization-sensitive optical coherence tomography (PS-OCT) to detect SRFib within retinal lesions by measurement of its birefringent collagen fibers. Methods : Twenty-five patients were enrolled with retinal pathology in one or both eyes containing (1) suspected SRFib, (2) lesions suspected not to be fibrotic, or (3) lesions with doubtful presence of SRFib. All eyes were evaluated for SRFIb using conventional diagnostics by three retinal specialists. PS-OCT images were visually evaluated for SRFib based on cumulative phase ...

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    14. Assessment of Generative Adversarial Networks Model for Synthetic Optical Coherence Tomography Images of Retinal Disorders

      Assessment of Generative Adversarial Networks Model for Synthetic Optical Coherence Tomography Images of Retinal Disorders

      Purpose : To assess whether a generative adversarial network (GAN) could synthesize realistic optical coherence tomography (OCT) images that satisfactorily serve as the educational images for retinal specialists, and the training datasets for the classification of various retinal disorders using deep learning (DL). Methods : The GANs architecture was adopted to synthesize high-resolution OCT images trained on a publicly available OCT dataset, including urgent referrals (37,206 OCT images from eyes with choroidal neovascularization, and 11,349 OCT images from eyes with diabetic macular edema) and nonurgent referrals (8617 OCT images from eyes with drusen, and 51,140 OCT images from normal ...

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    15. OCT Angiography to Predict Geographic Atrophy Progression using Choriocapillaris Flow Void as a Biomarker

      OCT Angiography to Predict Geographic Atrophy Progression using Choriocapillaris Flow Void as a Biomarker

      Purpose : To investigate the relationship between choriocapillaris (CC) flow void (FV) percentage and geographic atrophy (GA) growth rate, and study how variations in FV percentage surrounding GA predict regional GA growth. Methods : This prospective, longitudinal study enrolled subjects with GA secondary to nonexudative age-related macular degeneration. Optical coherence tomography angiography imaged the CC and FV percentage was evaluated using a validated algorithm. GA growth rate was measured as the difference in the square root of GA area divided by the months between baseline and follow-up imaging. Results : Twelve eyes from 7 subjects with a mean age of 80 ± 5 years ...

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    16. High-Speed, Ultrahigh-Resolution Spectral-Domain OCT with Extended Imaging Range Using Reference Arm Length Matching

      High-Speed, Ultrahigh-Resolution Spectral-Domain OCT with Extended Imaging Range Using Reference Arm Length Matching

      Purpose : To develop high-speed, extended-range, ultrahigh-resolution spectral-domain optical coherence tomography (UHR SD-OCT) and demonstrate scan protocols for clinical retinal imaging. Methods : A UHR SD-OCT operating at 840-nm with 150-nm bandwidths was developed. The axial imaging range was extended by dynamically matching reference arm length to the retinal contour during acquisition. Two scan protocols were demonstrated for imaging healthy participants and patients with dry age-related macular degeneration. A high-definition raster protocol with intra–B-scan reference arm length matching (ReALM) was used for high-quality cross-sectional imaging. A cube volume scan using horizontal and vertical rasters with inter–B-scan ReALM and software motion ...

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    17. Impact of Scan Tilt on Quantitative Assessments Using Optical Coherence Tomography Angiography

      Impact of Scan Tilt on Quantitative Assessments Using Optical Coherence Tomography Angiography

      Purpose : To investigate the impact of scan tilt on quantitative assessments using swept-source optical coherence tomography angiography (SS-OCTA) in healthy participants. Methods : Healthy participants were imaged with a SS-OCTA system (PLEX Elite 9000; Carl Zeiss Meditec, Inc, Dublin, CA). After a standard scan was obtained, tilted scans were obtained by moving the optical coherence tomography beam entrance position horizontally. The tilting angle was measured from the B-scan image, and the flattest (horizontal) and the most tilted images were selected for comparative analysis. Foveal avascular zone (FAZ) area, vessel density (VD), and vessel length density (VLD) from the superficial and deep ...

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    18. Comparison of Rates of Progression of Macular OCT Measures in Glaucoma

      Comparison of Rates of Progression of Macular OCT Measures in Glaucoma

      Purpose : The purpose of this study was to compare rates of change of various macular thickness measures and evaluate the influence of baseline damage on macular rates of change. Methods : One hundred twelve eyes (112 patients) with ≥ 2 years of follow-up and ≥ 5 macular optical coherence tomography (OCT) images and 10-2 visual field (VF) tests were included. OCT measures of interests were full macular thickness (FMT), ganglion cell complex (GCC), ganglion cell/inner plexiform layer (GCIPL), ganglion cell layer (GCL), and outer retinal layer (ORL) thickness in 3° × 3° superpixels. Rates of change were estimated with linear regression and normalized ...

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      Mentions: UCLA
    19. Artificial Intelligence Mapping of Structure to Function in Glaucoma

      Artificial Intelligence Mapping of Structure to Function in Glaucoma

      Purpose : To develop an artificial intelligence (AI)–based structure-function (SF) map relating retinal nerve fiber layer (RNFL) damage on spectral domain optical coherence tomography (SDOCT) to functional loss on standard automated perimetry (SAP). Methods : The study included 26,499 pairs of SAP and SDOCT from 15,173 eyes of 8878 patients with glaucoma or suspected of having the disease extracted from the Duke Glaucoma Registry. The data set was randomly divided at the patient level in training and test sets. A convolutional neural network (CNN) was initially trained and validated to predict the 52 sensitivity threshold points of the 24-2 ...

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    20. Fast and Automated Hyperreflective Foci Segmentation Based on Image Enhancement and Improved 3D U-Net in SD-OCT Volumes with Diabetic Retinopathy

      Fast and Automated Hyperreflective Foci Segmentation Based on Image Enhancement and Improved 3D U-Net in SD-OCT Volumes with Diabetic Retinopathy

      Purpose : To design a robust and automated hyperreflective foci (HRF) segmentation framework for spectral-domain optical coherence tomography (SD-OCT) volumes, especially volumes with low HRF-background contrast. Methods : HRF in retinal SD-OCT volumes appear with low-contrast characteristics that results in the difficulty of HRF segmentation. Therefore to effectively segment the HRF we proposed a fully automated method for HRF segmentation in SD-OCT volumes with diabetic retinopathy (DR). First, we generated the enhanced SD-OCT images from the denoised SD-OCT images with an enhancement method. Then the enhanced images were cascaded with the denoised images as the two-channel input to the network against the ...

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    21. A Deep-Learning Approach for Automated OCT En-Face Retinal Vessel Segmentation in Cases of Optic Disc Swelling Using Multiple En-Face Images as Input

      A Deep-Learning Approach for Automated OCT En-Face Retinal Vessel Segmentation in Cases of Optic Disc Swelling Using Multiple En-Face Images as Input

      Purpose : In cases of optic disc swelling, segmentation of projected retinal blood vessels from optical coherence tomography (OCT) volumes is challenging due to swelling-based shadowing artifacts. Based on our hypothesis that simultaneously considering vessel information from multiple projected retinal layers can substantially increase vessel visibility, in this work, we propose a deep-learning-based approach to segment vessels involving the simultaneous use of three OCT en-face images as input. Methods : A human expert vessel tracing combining information from OCT en-face images of the retinal pigment epithelium (RPE), inner retina, and total retina as well as a registered fundus image served as the ...

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    22. The Impact of Deterministic Signal Loss on OCT Angiography Measurements

      The Impact of Deterministic Signal Loss on OCT Angiography Measurements

      Purpose : In this study, we aimed at investigating the impact of deterministic signal loss on image quality and, thus, on optical coherence tomography angiography (OCTA) measurements performed by the RTVue-XR Avanti System. Methods : Absorptive filters with different optical densities (ODs) were used to simulate signal loss in a controlled way in 30 eyes from 15 healthy subjects. Scan Quality (SQ), provided by the AngioVue software, was applied as a measure of image quality. Results : Assessing the effect of decreased light transmittance on SQ values as well as that of attenuated image quality on OCTA parameters revealed a strong systematic dependence ...

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    23. Auto-Processed Retinal Vessel Shadow View Images From Bedside Optical Coherence Tomography to Evaluate Plus Disease in Retinopathy of Prematurity

      Auto-Processed Retinal Vessel Shadow View Images From Bedside Optical Coherence Tomography to Evaluate Plus Disease in Retinopathy of Prematurity

      Abstract Purpose : To describe the creation of en face retinal vessel shadow view (RVSV) optical coherence tomography (OCT) images and assess the feasibility of using these for evaluating vascular disease in preterm infants at risk for retinopathy of prematurity (ROP). Methods : In this exploratory study, we selected images from eyes with a range of ROP vascular disease, prospectively acquired from preterm infants using an investigational, noncontact, handheld, bedside swept-source OCT. We autosegmented OCT volumes using custom infant-specific software, extracted RVSV-OCT images from volumetric data bracketed around the retinal pigment epithelium, and automontaged the resulting RVSV-OCT images. Three masked ophthalmologists graded ...

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    24. Spectral-Domain Optical Coherence Tomography Is More Sensitive for Hydroxychloroquine-Related Structural Abnormalities Than Short-Wavelength and Near-Infrared Autofluorescence

      Spectral-Domain Optical Coherence Tomography Is More Sensitive for Hydroxychloroquine-Related Structural Abnormalities Than Short-Wavelength and Near-Infrared Autofluorescence

      Purpose : To analyze the appearance of structural abnormalities due to hydroxychloroquine (HCQ) toxicity by spectral-domain optical coherence tomography (SD-OCT) and short-wavelength autofluorescence (SW-AF) and near-infrared fundus autofluorescence (NIR-AF) imaging. Methods : This retrospective cohort study included 88 eyes from 44 patients who had a history of or were currently taking HCQ. SD-OCT, SW-AF, and NIR-AF images were analyzed by two independent graders for the detection of HCQ-associated abnormalities. Results : Sixty eyes (30 patients, 68%) presented with no abnormalities for either imaging modality. Twenty eyes (10 patients, 23%) presented with parafoveal abnormalities (ellipsoid zone attenuation and/or interdigitation zone continuity loss) in ...

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