ARTIFICIAL INTELLIGENCE FOR OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY-BASED DISEASE ACTIVITY PREDICTION IN AGE-RELATED MACULAR DEGENERATION.

PURPOSE: The authors hypothesize that optical coherence tomography angiography (OCTA)-visualized vascular morphology may be a predictor of choroidal neovascularization status in age-related macular degeneration (AMD). The authors thus evaluated the use of artificial intelligence (AI) to predict different stages of AMD disease based on OCTA en face 2D projections scans. METHODS: Retrospective cross-sectional study based on collected 2D OCTA data from 310 high-resolution scans. Based on OCT B-scan fluid and clinical status, OCTA was classified as normal, dry AMD, wet AMD active, and wet AMD in remission with no signs of activity. Two human experts graded the same test set, and a consensus grading between two experts was used for the prediction of four categories. RESULTS: The AI can achieve 80.36% accuracy on a four-category grading task with 2D OCTA projections. The sensitivity of prediction by AI was 0.7857 (active), 0.7142 (remission), 0.9286 (dry AMD), and 0.9286 (normal) and the specificity was 0.9524, 0.9524, 0.9286, and 0.9524, respectively. The sensitivity of prediction by human experts was 0.4286 active choroidal neovascularization, 0.2143 remission, 0.8571 dry AMD, and 0.8571 normal with specificity of 0.7619, 0.9286, 0.7857, and 0.9762, respectively. The overall AI classification prediction was significantly better than the human (odds ratio = 1.95, P = 0.0021). CONCLUSION: These data show that choroidal neovascularization morphology can be used to predict disease activity by AI; longitudinal studies are needed to better understand the evolution of choroidal neovascularization and features that predict reactivation. Future studies will be able to evaluate the additional predicative value of OCTA on top of other imaging characteristics (i.e., fluid location on OCT B scans) to help predict response to treatment.

Ultra-wide field and new wide field composite retinal image registration with AI-enabled pipeline and 3D distortion correction algorithm.

PURPOSE: This study aimed to compare a new Artificial Intelligence (AI) method to conventional mathematical warping in accurately overlaying peripheral retinal vessels from two different imaging devices: confocal scanning laser ophthalmoscope (cSLO) wide-field images and SLO ultra-wide field images. METHODS: Images were captured using the Heidelberg Spectralis 55-degree field-of-view and Optos ultra-wide field. The conventional mathematical warping was performed using Random Sample Consensus-Sample and Consensus sets (RANSAC-SC). This was compared to an AI alignment algorithm based on a one-way forward registration procedure consisting of full Convolutional Neural Networks (CNNs) with Outlier Rejection (OR CNN), as well as an iterative 3D camera pose optimization process (OR CNN + Distortion Correction [DC]). Images were provided in a checkerboard pattern, and peripheral vessels were graded in four quadrants based on alignment to the adjacent box. RESULTS: A total of 660 boxes were analysed from 55 eyes. Dice scores were compared between the three methods (RANSAC-SC/OR CNN/OR CNN + DC): 0.3341/0.4665/4784 for fold 1-2 and 0.3315/0.4494/4596 for fold 2-1 in composite images. The images composed using the OR CNN + DC have a median rating of 4 (out of 5) versus 2 using RANSAC-SC. The odds of getting a higher grading level are 4.8 times higher using our OR CNN + DC than RANSAC-SC (p < 0.0001). CONCLUSION: Peripheral retinal vessel alignment performed better using our AI algorithm than RANSAC-SC. This may help improve co-localizing retinal anatomy and pathology with our algorithm.

Choroidal Detachment After Intravitreal Injection of Faricimab.

This case report discusses a diagnosis of choroidal detachment and suprachoroidal hemorrhage in a patient aged 70 years after an uneventful intravitreal injection of faricimab for neovascular age-related macular degeneration.

The Sensitivity of Ultra-Widefield Fundus Photography Versus Scleral Depressed Examination for Detection of Retinal Horseshoe Tears.

PURPOSE: Ultra-widefield (UWF) imaging is commonly used in ophthalmology in tandem with scleral depressed examinations (SDE) to evaluate peripheral retinal disease. Because of the increased reliance on this technology in tele-ophthalmology, it is critical to evaluate its efficacy for detecting the peripheral retina when performed in isolation. Therefore, we sought to evaluate UWF imaging sensitivity in detecting retinal horseshoe tears (HSTs). STUDY DESIGN: Retrospective clinical validity and reliability study. METHODS: A single-institutional retrospective analysis was performed on patients at the Shiley Eye Institute, University of California, San Diego. Patients with HSTs seen on SDE who underwent treatment with laser were included in the study. A total of 140 patients with HSTs in the right and/or left eyes met the inclusion criteria. Those with concomitant ruptured globes, retinal detachments, and vitreous hemorrhages were excluded. A total of 123 patients with 135 HSTs were included in the final analysis. The primary outcome was the number of HSTs detected by UWF imaging. A secondary outcome was HST location. Sensitivity was measured with respect to HST location, and statistical significance was calculated by Fisher exact testing. RESULTS: A total of 69 (51.1%) HSTs were visualized on UWF images and 66 (48.9%) were not visualized. The sensitivity of UWF imaging in capturing HSTs was 7 of 41 (17.1%), 8 of 25 (32.0%), 7 of 14 (50.0%), and 47 of 55 (85.5%) for the superior, inferior, nasal, and temporal quadrants, respectively. Sensitivities between HST visibility and location were statistically significant (P < .001). CONCLUSIONS: Nearly half of HSTs were missed by UWF imaging. This study demonstrates that UWF imaging alone is not sufficiently sensitive to exclude the presence of HSTs.

Inner Retinal Thickness and Vasculature in Patients with Reticular Pseudodrusen.

INTRODUCTION: The aim of this study was to investigate retinal layer thickness and vessel density differences between patients with reticular pseudodrusen (RPD) and intermediate dry age-related macular degeneration (iAMD). METHODS: Participants included in the study were patients diagnosed by retinal specialists with RPD, iAMD, and both RPD and iAMD at our academic referral center, seen from May 2021 until February 2022. The central 3 mm retinal thickness was measured using spectral-domain optical coherence tomography (Heidelberg Spectralis HRA+OCT System; Heidelberg Engineering, Heidelberg, Germany). Individual retinal thickness measurements were obtained from the innermost layer (nerve fiber layer) until the outermost layer (retinal pigment epithelium [RPE]). Each thickness measurement was subdivided into nine Early Treatment Diabetic Retinopathy Study (ETDRS) sectors. For the vessel density, OCT angiography from the Heidelberg Spectralis System was measured using proprietary third-party software (AngioTool; National Institutes of Health, National Cancer Institute, Bethesda, MD). Clinical and demographic characteristics were compared across the three groups (iAMD, RPD, iAMD and RPD) and analyzed with necessary adjustments. Linear mixed-effects models with necessary corrections were employed to compare continuous eye-level measurements between our three groups as well as in pairwise fashion using the R statistical programming software (R version 4.2.1). RESULTS: A total of 25 eyes of 17 patients with RPD, 20 eyes of 15 patients with iAMD, and 14 eyes of 9 patients with both iAMD and RPD were analyzed. Retinal thickness analysis identified that the superior inner (p = 0.028) and superior outer (p = 0.027) maculas of eyes with both iAMD and RPD were significantly thinner than those with iAMD alone. In eyes with RPD, the superior inner and superior outer RPE (p = 0.011 and p = 0.05, respectively), outer plexiform layer (p = 0.003 and p = 0.013, respectively), and inner nuclear layer (p = 0.034 and p = 0, respectively) were noted to be thinner compared to eyes with iAMD alone. In addition, the macular deep capillary plexus vessel density was significantly reduced in eyes with RPD compared to eyes with iAMD (p = 0.017). CONCLUSION: Patients with RPD had inner retinal structural as well as vascular changes compared to iAMD patients. Inner retinal vascular attenuation should be investigated further to see if there is a causal association with retinal thinning.

REFINING THE RETINAL PHENOTYPE OF PATIENTS WITH SUSPECTED PENTOSAN POLYSULFATE SODIUM RETINOPATHY.

PURPOSE: To refine the retinal phenotypes of suspected pentosan polysulfate sodium toxicity using ultra-widefield imaging. METHODS: Patients with complete dosing profiles who visited the ophthalmology department and with ultra-widefield and optical coherence tomography imaging records were identified using electronic health records at a large academic center. Retinal toxicity was initially identified using previously published imaging criteria, while grading was categorized using both previously reported and new classification systems. RESULTS: One hundred and four patients were included in this study. Twenty-six (25%) were identified as having toxicity from PPS. The mean duration of exposure and cumulative dose between the retinopathy group (162.7 months, 1,803.2 g) were longer and higher compared with the nonretinopathy group (69.7 months, 972.6 g) (both P < 0.001). There was variability of extramacular phenotype in the retinopathy group, with four eyes having only peripapillary involvement and six eyes having far peripheral extension. CONCLUSION: Retinal toxicity in the setting of prolonged exposure and increased cumulative dosing from PPS therapy produces phenotypic variability. Providers should be aware of the extramacular component of toxicity when screening patients. Understanding the different retinal phenotypes may prevent continued exposure and reduce the risk of vision-threatening foveal-involving disease.

Efficacy and accuracy of artificial intelligence to overlay multimodal images from different optical instruments in patients with retinitis pigmentosa.

BACKGROUND: Retinitis pigmentosa (RP) represents a group of progressive, genetically heterogenous blinding diseases. Recently, relationships between measures of retinal function and structure are needed to help identify outcome measures or biomarkers for clinical trials. The ability to align retinal multimodal images, taken on different platforms, will allow better understanding of this relationship. We investigate the efficacy of artificial intelligence (AI) in overlaying different multimodal retinal images in RP patients. METHODS: We overlayed infrared images from microperimetry on near-infra-red images from scanning laser ophthalmoscope and spectral domain optical coherence tomography in RP patients using manual alignment and AI. The AI adopted a two-step framework and was trained on a separate dataset. Manual alignment was performed using in-house software that allowed labelling of six key points located at vessel bifurcations. Manual overlay was considered successful if the distance between same key points on the overlayed images was ≤1/2°. RESULTS: Fifty-seven eyes of 32 patients were included in the analysis. AI was significantly more accurate and successful in aligning images compared to manual alignment as confirmed by linear mixed-effects modelling (p < 0.001). A receiver operating characteristic analysis, used to compute the area under the curve of the AI (0.991) and manual (0.835) Dice coefficients in relation to their respective 'truth' values, found AI significantly more accurate in the overlay (p < 0.001). CONCLUSION: AI was significantly more accurate than manual alignment in overlaying multimodal retinal imaging in RP patients and showed the potential to use AI algorithms for future multimodal clinical and research applications.

Randomized Phase IIb Study of Brimonidine Drug Delivery System Generation 2 for Geographic Atrophy in Age-Related Macular Degeneration.

PURPOSE: To evaluate the safety and efficacy of repeat injections of Brimonidine Drug Delivery System (Brimo DDS) Generation 2 (Gen 2) containing 400-µg brimonidine in patients with geographic atrophy (GA) secondary to age-related macular degeneration (AMD). DESIGN: A phase IIb, randomized, multicenter, double-masked, sham-controlled, 30-month study (BEACON). PARTICIPANTS: Patients diagnosed with GA secondary to AMD and multifocal lesions with total area of > 1.25 mm2 and ≤ 18 mm2 in the study eye. METHODS: Enrolled patients were randomized to treatment with intravitreal injections of 400-µg Brimo DDS (n = 154) or sham procedure (n = 156) in the study eye every 3 months from day 1 to month 21. MAIN OUTCOME MEASURES: The primary efficacy endpoint was GA lesion area change from baseline in the study eye, assessed with fundus autofluorescence imaging, at month 24. RESULTS: The study was terminated early, at the time of the planned interim analysis, because of a slow GA progression rate (∼ 1.6 mm2/year) in the enrolled population. Least squares mean (standard error) GA area change from baseline at month 24 (primary endpoint) was 3.24 (0.13) mm2 with Brimo DDS (n = 84) versus 3.48 (0.13) mm2 with sham (n = 91), a reduction of 0.25 mm2 (7%) with Brimo DDS compared with sham (P = 0.150). At month 30, GA area change from baseline was 4.09 (0.15) mm2 with Brimo DDS (n = 49) versus 4.52 (0.15) mm2 with sham (n = 46), a reduction of 0.43 mm2 (10%) with Brimo DDS compared with sham (P = 0.033). Exploratory analysis showed numerically smaller loss over time in retinal sensitivity assessed with scotopic microperimetry with Brimo DDS than with sham (P = 0.053 at month 24). Treatment-related adverse events were usually related to the injection procedure. No implant accumulation was observed. CONCLUSIONS: Multiple intravitreal administrations of Brimo DDS (Gen 2) were well tolerated. The primary efficacy endpoint at 24 months was not met, but there was a numeric trend for reduction in GA progression at 24 months compared with sham treatment. The study was terminated early because of the lower-than-expected GA progression rate in the sham/control group. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosures may be found after the references.

PENTOSAN POLYSULFATE SODIUM (ELMIRON) MACULOPATHY: A Genetic Perspective.

PURPOSE: To assess genetic associations for pentosan polysufate sodium maculopathy. METHODS: Genetic testing for inherited retinal dystrophy genes using exome testing and for 14 age-related macular degeneration-associated single nucleotide polymorphisms (SNPs) using panel testing were performed. In addition, full-field electroretinograms (ffERG) were obtained to identify any cone-rod dystrophy. RESULTS: Eleven of 15 patients were women, with a mean age of 69 (range 46-85). Inherited retinal dystrophy exome testing in five patients revealed six pathogenic variants, but failed to confirm inherited retinal dystrophy in any patient genetically. FfERG performed in 12 patients demonstrated only nonspecific a- and b-wave abnormalities in 11 cases and was normal in one case. For age-related macular degeneration single nucleotide polymorphisms, CFH rs3766405 ( P = 0.003) and CETP ( P = 0.027) were found to be statistically significantly associated with pentosan polysulfate maculopathy phenotype compared with the control population. CONCLUSION: Pentosan polysulfate maculopathy is not associated with Mendelian inherited retinal dystrophy genes. However, several age-related macular degeneration risk alleles were identified to be associated with maculopathy compared with their frequency in the normal population. This suggests a role for genes in disease pathology, particularly the alternative complement pathway. These findings would benefit from further investigation to understand the risk of developing maculopathy in taking pentosan polysulfate.

Retinal tissue and microvasculature loss in COVID-19 infection.

This cross-sectional study aimed to investigate the hypothesis that permanent capillary damage may underlie the long-term COVID-19 sequela by quantifying the retinal vessel integrity. Participants were divided into three subgroups; Normal controls who had not been affected by COVID-19, mild COVID-19 cases who received out-patient care, and severe COVID-19 cases requiring intensive care unit (ICU) admission and respiratory support. Patients with systemic conditions that may affect the retinal vasculature before the diagnosis of COVID-19 infection were excluded. Participants underwent comprehensive ophthalmologic examination and retinal imaging obtained from Spectral-Domain Optical Coherence Tomography (SD-OCT), and vessel density using OCT Angiography. Sixty-one eyes from 31 individuals were studied. Retinal volume was significantly decreased in the outer 3 mm of the macula in the severe COVID-19 group (p = 0.02). Total retinal vessel density was significantly lower in the severe COVID-19 group compared to the normal and mild COVID-19 groups (p = 0.004 and 0.0057, respectively). The intermediate and deep capillary plexuses in the severe COVID-19 group were significantly lower compared to other groups (p < 0.05). Retinal tissue and microvascular loss may be a biomarker of COVID-19 severity. Further monitoring of the retina in COVID-19-recovered patients may help further understand the COVID-19 sequela.

DIRECT MACULAR HOLE MANIPULATION RESULTS IN HIGH SUCCESS RATE IN SECONDARY MACULAR HOLE REPAIR.

PURPOSE: To investigate closure rates and functional outcomes of surgery for refractory and recurrent macular holes (MHs) in a real-world setting. METHODS: Retrospective review of secondary MH surgeries. RESULTS: A total of 72 eyes from 72 patients were included. Eyes had a mean of 1.51 surgeries before inclusion into this study with a mean MH size of 762 µ m and a mean baseline logarithm of the minimum angle of resolution best-corrected visual acuity of 1.11 (∼20/260 Snellen). Closure rates were 89.3% for tissue transplantation, 77.3% for internal limiting membrane (ILM) flaps, 92.9% for MH manipulation, and 12.5% for repeat ILM peeling ( P < 0.05). Best-corrected visual acuity changes in logarithm of the minimum angle of resolution from baseline to postoperative month six were +0.29 for ILM peeling alone (15 Early Treatment Diabetic Retinopathy Study letters worse), -0.39 for MH manipulation (20 Early Treatment Diabetic Retinopathy Study letters improved), -0.23 for tissue transplantation (13 Early Treatment Diabetic Retinopathy Study letters improved), and -0.2 for ILM flaps (10 Early Treatment Diabetic Retinopathy Study letters improved; P < 0.05). CONCLUSION: Secondary MH closure is possible using various surgical techniques with acceptable anatomical closure rates. Repeat ILM peeling is associated with the lowest closure rates and poorest functional results. To distinguish between techniques would require a large sample size of approximately 750 eyes.

Accuracy and Time Comparison Between Side-by-Side and Artificial Intelligence Overlayed Images.

BACKGROUND AND OBJECTIVE: The purpose of this study was to evaluate the accuracy and the time to find a lesion, taken in different platforms, color fundus photographs and infrared scanning laser ophthalmoscope images, using the traditional side-by-side (SBS) colocalization technique to an artificial intelligence (AI)-assisted technique. PATIENTS AND METHODS: Fifty-three pathological lesions were studied in 11 eyes. Images were aligned using SBS and AI overlaid methods. The location of each color fundus lesion on the corresponding infrared scanning laser ophthalmoscope image was analyzed twice, one time for each method, on different days, for two specialists, in random order. The outcomes for each method were measured and recorded by an independent observer. RESULTS: The colocalization AI method was superior to the conventional in accuracy and time (P < .001), with a mean time to colocalize 37% faster. The error rate using AI was 0% compared with 18% in SBS measurements. CONCLUSIONS: AI permitted a more accurate and faster colocalization of pathologic lesions than the conventional method. [Ophthalmic Surg Lasers Imaging Retina 2023;54:108-113.].

Retinal vein occlusion is associated with stroke independent of underlying cardiovascular disease.

BACKGROUND: Stroke is a leading cause of mortality and morbidity. Thus, identifying associated risk factors may lead to earlier interventions aimed at reducing the risk of stroke development. Since cardiovascular disease simultaneously increases the risk of stroke and retinal vein occlusion (RVO), we sought to determine whether RVO is associated with the risk of stroke independent of underlying cardiovascular co-morbidities. METHODS: In this cross-sectional study, we reviewed the records of 80,754 individuals who were evaluated by an ophthalmologist over a 6-year period. We identified individuals with RVO, stroke and cardiovascular diseases including hypertension, diabetes mellitus, carotid disease, coronary artery disease and atrial fibrillation. Multivariable logistic regression models were used to analyze odds ratios for RVO and stroke. RESULTS: After adjusting for age, sex, cardiovascular disease and other risk factors, we found that the presence of RVO was associated with an odds ratio for stroke of 1.73 (CI, 1.40-2.12, p < 0.001). The association between RVO and stroke, after adjusting for sex and cardiovascular co-morbidities, was significantly stronger in individuals younger than 50 years of age, with an odds ratio of having a stroke of 3.06 (1.34-6.25, p < 0.001), while the presence of RVO in individuals older than 85 years was not significantly associated with stroke 1.19 (0.77-1.79, p = 0.41). CONCLUSIONS: Our findings demonstrate that RVO is significantly associated with stroke, even after adjusting for underlying cardiovascular co-morbidities. This association was highly significant in younger subjects, while not significant in older individuals.

Comparison of multicolor scanning laser imaging and color fundus photography in evaluating vessel whitening in branch retinal vein occlusion.

INTRODUCTION: Few studies have explored Multicolor™ imaging (MCI) in evaluating retinal vascular diseases, particularly branch retinal vein occlusion (BRVO). This study aimed to compare the identification of retinal vessel whitening in BRVO using MCI by scanning confocal laser versus conventional white flash color fundus photography (CFP). METHODS: Paired images of consecutive patients diagnosed with BRVO who underwent same-day MCI and CFP were reviewed. Visualization of vessel whitening on MCI and CFP was graded and scored using a scale by two masked graders. A longitudinal analysis of the vessel grading score was performed to evaluate the vessel whitening detection by MCI. A correlation analysis was conducted between vessel whitening on MCI and the measured area of retinal ischemia on fluorescein angiography to evaluate the MCI performance. RESULTS: Forty-four eyes of 41 patients (mean age 69±14 years; 61% female) were analyzed. MCI demonstrated superior vessel whitening visibility score than CFP (p<0.001). Longitudinal analysis showed no significant changes in vessel whitening visibility scores over a mean follow-up time of 430 ± 648 days (p=0.655). There was a significantly positive correlation between the grading score of vessels whitening by MCI and the area of ischemia by fluorescein angiography (r2=0.15; p=0.036). CONCLUSION: MCI appears to provide a superior detection of whitening BRVO compared to CFP, serving as a rapid and non-invasive correlate of retinal ischemia.

JOINT MOTION CORRECTION AND 3D SEGMENTATION WITH GRAPH-ASSISTED NEURAL NETWORKS FOR RETINAL OCT.

Optical Coherence Tomography (OCT) is a widely used non-invasive high resolution 3D imaging technique for biological tissues and plays an important role in ophthalmology. OCT retinal layer segmentation is a fundamental image processing step for OCT-Angiography projection, and disease analysis. A major problem in retinal imaging is the motion artifacts introduced by involuntary eye movements. In this paper, we propose neural networks that jointly correct eye motion and retinal layer segmentation utilizing 3D OCT information, so that the segmentation among neighboring B-scans would be consistent. The experimental results show both visual and quantitative improvements by combining motion correction and 3D OCT layer segmentation comparing to conventional and deep-learning based 2D OCT layer segmentation.

Effective treatment of retinal neovascular leakage with fusogenic porous silicon nanoparticles delivering VEGF-siRNA.

Aim: To evaluate an intravitreally injected nanoparticle platform designed to deliver VEGF-A siRNA to inhibit retinal neovascular leakage as a new treatment for proliferative diabetic retinopathy and diabetic macular edema. Materials & methods: Fusogenic lipid-coated porous silicon nanoparticles loaded with VEGF-A siRNA, and pendant neovascular integrin-homing iRGD, were evaluated for efficacy by intravitreal injection in a rabbit model of retinal neovascularization. Results: For 12 weeks post-treatment, a reduction in vascular leakage was observed for treated diseased eyes versus control eyes (p = 0.0137), with a corresponding reduction in vitreous VEGF-A. Conclusion: Fusogenic lipid-coated porous silicon nanoparticles siRNA delivery provides persistent knockdown of VEGF-A and reduced leakage in a rabbit model of retinal neovascularization as a potential new intraocular therapeutic.

Two-Step Registration on Multi-Modal Retinal Images via Deep Neural Networks.

Multi-modal retinal image registration plays an important role in the ophthalmological diagnosis process. The conventional methods lack robustness in aligning multi-modal images of various imaging qualities. Deep-learning methods have not been widely developed for this task, especially for the coarse-to-fine registration pipeline. To handle this task, we propose a two-step method based on deep convolutional networks, including a coarse alignment step and a fine alignment step. In the coarse alignment step, a global registration matrix is estimated by three sequentially connected networks for vessel segmentation, feature detection and description, and outlier rejection, respectively. In the fine alignment step, a deformable registration network is set up to find pixel-wise correspondence between a target image and a coarsely aligned image from the previous step to further improve the alignment accuracy. Particularly, an unsupervised learning framework is proposed to handle the difficulties of inconsistent modalities and lack of labeled training data for the fine alignment step. The proposed framework first changes multi-modal images into a same modality through modality transformers, and then adopts photometric consistency loss and smoothness loss to train the deformable registration network. The experimental results show that the proposed method achieves state-of-the-art results in Dice metrics and is more robust in challenging cases.

Perspective Distortion Correction for Multi-Modal Registration between Ultra-Widefield and Narrow-Angle Retinal Images.

Multi-modal retinal image registration between 2D Ultra-Widefield (UWF) and narrow-angle (NA) images has not been well-studied, since most existing methods mainly focus on NA image alignment. The stereographic projection model used in UWF imaging causes strong distortions in peripheral areas, which leads to inferior alignment quality. We propose a distortion correction method that remaps the UWF images based on estimated camera view points of NA images. In addition, we set up a CNN-based registration pipeline for UWF and NA images, which consists of the distortion correction method and three networks for vessel segmentation, feature detection and matching, and outlier rejection. Experimental results on our collected dataset shows the effectiveness of the proposed pipeline and the distortion correction method.

Assessing the validity of a cross-platform retinal image segmentation tool in normal and diseased retina.

Comparing automated retinal layer segmentation using proprietary software (Heidelberg Spectralis HRA + OCT) and cross-platform Optical Coherence Tomography (OCT) segmentation software (Orion). Image segmentations of normal and diseased (iAMD, DME) eyes were performed using both softwares and then compared to the 'gold standard' of manual segmentation. A qualitative assessment and quantitative (layer volume) comparison of segmentations were performed. Segmented images from the two softwares were graded by two masked graders and in cases with difference, a senior retina specialist made a final independent decisive grading. Cross-platform software was significantly better than the proprietary software in the segmentation of NFL and INL layers in Normal eyes. It generated significantly better segmentation only for NFL in iAMD and for INL and OPL layers in DME eyes. In normal eyes, all retinal layer volumes calculated by the two softwares were moderate-strongly correlated except OUTLY. In iAMD eyes, GCIPL, INL, ONL, INLY, TRV layer volumes were moderate-strongly correlated between softwares. In eyes with DME, all layer volume values were moderate-strongly correlated between softwares. Cross-platform software can be used reliably in research settings to study the retinal layers as it compares well against manual segmentation and the commonly used proprietary software for both normal and diseased eyes.