On the public citation graph
Detection of Glaucoma Using Cup to Disc Ratio From Spectral Domain Optical Coherence Tomography Images
0 signed · 89 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1001/archopht.118.8.1105openalex-snapshot
The Prevalence of Glaucoma in Chinese Residents of Singapore A Cross-Sectional Population Survey of the Tanjong Pagar District
inferredcites →https://doi.org/10.1007/978-0-387-76700-0openalex-snapshot
The glaucoma book : a practical, evidence-based approach to patient care
inferredcites →https://doi.org/10.1007/978-0-387-76700-0_1openalex-snapshot
Glaucoma in the Twenty-First Century
inferredcites →https://doi.org/10.1016/j.ajo.2004.08.036openalex-snapshot
Comparison of three optical coherence tomography scanning areas for detection of glaucomatous damage
inferredcites →https://doi.org/10.1016/j.ajo.2008.06.010openalex-snapshot
Thickness Profiles of Retinal Layers by Optical Coherence Tomography Image Segmentation
inferredcites →https://doi.org/10.1016/j.ophtha.2007.04.003openalex-snapshot
Incident Open-angle Glaucoma and Intraocular Pressure
inferredcites →https://doi.org/10.1016/j.ophtha.2014.04.030openalex-snapshot
Glaucoma Diagnostic Accuracy of Optical Coherence Tomography Parameters in Early Glaucoma with Different Types of Optic Disc Damage
inferredcites →https://doi.org/10.1016/s0002-9394(02)02093-7openalex-snapshot
Comparison of optic nerve head measurements obtained by optical coherence tomography and confocal scanning laser ophthalmoscopy
inferredcites →https://doi.org/10.1038/eye.2013.163openalex-snapshot
The comparison of manual vs automated disc margin delineation using spectral-domain optical coherence tomography
inferredcites →https://doi.org/10.1049/iet-ipr.2016.0812openalex-snapshot
Improved automated detection of glaucoma from fundus image using hybrid structural and textural features
inferredcites →https://doi.org/10.1097/00061198-199510000-00010openalex-snapshot
Basic Sciences in Clinical Glaucoma
inferredcites →https://doi.org/10.1097/iio.0b013e318187e93dopenalex-snapshot
Risk Assessment in Glaucoma and Ocular Hypertension
inferredcites →https://doi.org/10.1109/bmei.2013.6746926openalex-snapshot
Quantitative assessments of cup-to-disk ratios in spectral domain optical coherence tomography images for glaucoma diagnosis
inferredcites →https://doi.org/10.1109/tgrs.2010.2048116openalex-snapshot
Morphological Attribute Profiles for the Analysis of Very High Resolution Images
inferredcites →https://doi.org/10.1111/j.1475-1313.2004.00235.xopenalex-snapshot
A comparison of cup‐to‐disc ratio measurement in normal subjects using optical coherence tomography image analysis of the optic nerve head and stereo fundus biomicroscopy
inferredcites →https://doi.org/10.1145/1007996.1008036openalex-snapshot
Curve and surface interpolation and approximation
inferredcites →https://doi.org/10.1145/1026487.1008036openalex-snapshot
Curve and surface interpolation and approximation
inferredcites →https://doi.org/10.1167/iovs.04-1107openalex-snapshot
Analysis of Retinal Nerve Fiber Layer and Optic Nerve Head in Glaucoma with Different Reference Plane Offsets, Using Optical Coherence Tomography
inferredcites →https://doi.org/10.1167/iovs.08-1759openalex-snapshot
The Prevalence and Types of Glaucoma in Malay People: The Singapore Malay Eye Study
inferredcites →https://doi.org/10.1167/iovs.08-2302openalex-snapshot
Detection of Optic Nerve Head Neural Canal Opening within Histomorphometric and Spectral Domain Optical Coherence Tomography Data Sets
inferredcites →https://doi.org/10.1167/iovs.09-3586openalex-snapshot
Comparison of Clinical and Spectral Domain Optical Coherence Tomography Optic Disc Margin Anatomy
inferredcites →https://doi.org/10.1167/iovs.09-4838openalex-snapshot
Automated Segmentation of Neural Canal Opening and Optic Cup in 3D Spectral Optical Coherence Tomography Volumes of the Optic Nerve Head
inferredcites →https://doi.org/10.1364/josaa.24.001901openalex-snapshot
Speckle reduction in optical coherence tomography images using digital filtering
inferredcites →https://doi.org/10.1364/oe.18.011347openalex-snapshot
Automated volumetric evaluation of stereoscopic disc photography
inferredcites →https://doi.org/10.1364/oe.23.031216openalex-snapshot
Automated segmentation of optic disc in SD-OCT images and cup-to-disc ratios quantification by patch searching-based neural canal opening detection
inferredcites →https://doi.org/10.17485/ijst/2015/v8i24/80151openalex-snapshot
Analysis of Segmentation Algorithms in Colour Fundus and OCT Images for Glaucoma Detection
inferredcites →https://doi.org/10.3923/jas.2012.2128.2138openalex-snapshot
Automatic Detection of Glaucoma Using Optical Coherence Tomography Image
inferredcites →https://doi.org/10.4103/0301-4738.39112openalex-snapshot
Optic disc topography of normal Indian eyes: An assessment using optical coherence tomography
inferredcites →https://doi.org/10.5194/isprsarchives-xl-1-w1-29-2013openalex-snapshot
USING MORPHOLOGICAL DIFFERENTIAL ATTRIBUTE PROFILES FOR CHANGE CATEGORIZATION IN HIGH RESOLUTION SAR IMAGES
inferredcites →https://doi.org/10.5507/bp.2015.053openalex-snapshot
Optic nerve head segmentation using fundus images and optical coherence tomography images for glaucoma detection
inferredcites →https://doi.org/10.6688/jise.2001.17.5.1openalex-snapshot
A fast algorithm for multilevel thresholding
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.5281/zenodo.4420085openalex-extracted
Early and Efficient Detection of Glaucoma Using Image Processing and Deep Learning
inferred← citeshttps://doi.org/10.1002/ima.22435openalex-snapshot
Hybrid features and optimization‐driven recurrent neural network for glaucoma detection
inferred← citeshttps://doi.org/10.1007/978-3-030-15887-3_25openalex-snapshot
Automated Detection of Eye Related Diseases Using Digital Image Processing
inferred← citeshttps://doi.org/10.1007/978-3-030-49795-8_69openalex-snapshot
A Survey on Classification and Prediction of Glaucoma and AMD Based on OCT and Fundus Images
inferred← citeshttps://doi.org/10.1007/978-3-031-45392-2_30openalex-snapshot
Exploring Artificial Intelligence Methods for the Automatic Measurement of a New Biomarker Aiming at Glaucoma Diagnosis
inferred← citeshttps://doi.org/10.1007/978-3-031-65392-6_18openalex-snapshot
Glaucoma Diagnosis Based on Fusion of Shape and Texture Features from Neuroretinal Rim Area of Retinal Fundus Image
inferred← citeshttps://doi.org/10.1007/978-981-16-0708-0_26openalex-snapshot
Glaucoma Detection Using Features of Optic Nerve Head, CDR and ISNT from Fundus Image of Eye
inferred← citeshttps://doi.org/10.1007/978-981-96-1758-6_25openalex-snapshot
Detection of Glaucoma Using OCT Images
inferred← citeshttps://doi.org/10.1007/s10278-020-00383-5openalex-snapshot
Extraction of Retinal Layers Through Convolution Neural Network (CNN) in an OCT Image for Glaucoma Diagnosis
inferred← citeshttps://doi.org/10.1007/s10462-024-10736-zopenalex-snapshot
A comprehensive review of artificial intelligence models for screening major retinal diseases
inferred← citeshttps://doi.org/10.1007/s11042-021-11583-8openalex-snapshot
Segmentation of the optic disc and optic cup using a machine learning-based biregional contour evolution model for the cup-to-disc ratio
inferred← citeshttps://doi.org/10.1007/s11042-022-12178-7openalex-snapshot
Multi-modal active learning with deep reinforcement learning for target feature extraction in multi-media image processing applications
inferred← citeshttps://doi.org/10.1007/s11042-022-13540-5openalex-snapshot
RETRACTED ARTICLE: An IoT based predictive modeling for Glaucoma detection in optical coherence tomography images using hybrid genetic algorithm
inferred← citeshttps://doi.org/10.1016/b978-0-323-95415-0.00013-9openalex-snapshot
Classification of ocular diseases using transfer learning approaches and glaucoma severity grading
inferred← citeshttps://doi.org/10.1016/j.cmpb.2022.106801openalex-snapshot
Automatic Segmentation of the Optic Nerve Head Region in Optical Coherence Tomography: A Methodological Review
inferred← citeshttps://doi.org/10.1016/j.compbiomed.2022.106277openalex-snapshot
Recent trends and advances in fundus image analysis: A review
inferred← citeshttps://doi.org/10.1016/j.compmedimag.2019.101657openalex-snapshot
Glaucoma detection using image processing techniques: A literature review
inferred← citeshttps://doi.org/10.1016/j.dib.2020.105342openalex-snapshot
Data on OCT and fundus images for the detection of glaucoma
inferred← citeshttps://doi.org/10.1016/j.inffus.2022.12.006openalex-snapshot
Angular contrastive distillation driven self-supervised scanner independent screening and grading of retinopathy
inferred← citeshttps://doi.org/10.1016/j.optlastec.2019.105830openalex-snapshot
Automated segmentation of fluid regions in optical coherence tomography B-scan images of age-related macular degeneration
inferred← citeshttps://doi.org/10.1080/03772063.2022.2043783openalex-snapshot
Glaucoma Detection Using Optical Coherence Tomography Images: A Systematic Review of Clinical and Automated Studies
inferred← citeshttps://doi.org/10.1109/access.2018.2890544openalex-snapshot
Automatic Determination of Vertical Cup-to-Disc Ratio in Retinal Fundus Images for Glaucoma Screening
inferred← citeshttps://doi.org/10.1109/access.2021.3061451openalex-snapshot
A Review on Glaucoma Disease Detection Using Computerized Techniques
inferred← citeshttps://doi.org/10.1109/auteee50969.2020.9315604openalex-snapshot
Research on Feature Extraction Method of Fundus Image Based on Deep Learning
inferred← citeshttps://doi.org/10.1109/ce2ct64011.2025.10939651openalex-snapshot
An Enhanced Pre-Processing Technique For Eye Image Segmentation
inferred← citeshttps://doi.org/10.1109/cleo-pr62338.2022.10432359openalex-snapshot
Deep Learning for Automatic Detection of Neural Canal Opening in Optical Coherence Tomography Images
inferred← citeshttps://doi.org/10.1109/codit.2019.8820306openalex-snapshot
A Framework for Extraction of Inner Limiting Membrane in High Speckle Noisy Images
inferred← citeshttps://doi.org/10.1109/icaitpr51569.2022.9844194openalex-snapshot
Retracted: Diagnosis of Glaucoma from Retinal Fundus Image Using Deep Transfer Learning
inferred← citeshttps://doi.org/10.1109/icces63552.2024.10860263openalex-snapshot
Analysis of Cup to Disc Ratio Using Fundus and Optical Coherence Tomography Images
inferred← citeshttps://doi.org/10.1109/iccica52458.2021.9697135openalex-snapshot
GCL And ILM Layer Extraction From OCT Images For Glaucoma Detection
inferred← citeshttps://doi.org/10.1109/iccit63348.2025.10989306openalex-snapshot
An Improved Machine Learning-Driven Glaucoma Diagnostic Framework
inferred← citeshttps://doi.org/10.1109/iccsce61582.2024.10696203openalex-snapshot
PSO-optimized U-Net for Automatic Retinal Optic Disk Segmentation
inferred← citeshttps://doi.org/10.1109/icetea64585.2025.11099982openalex-snapshot
A Dilated Feature Fusion Approach to Optic Cup and Disc Segmentation for Glaucoma Detection and Progression Prediction
inferred← citeshttps://doi.org/10.1109/icodt255437.2022.9787418openalex-snapshot
A Review of Autonomous Glaucomatous Grading via OCT Imagery
inferred← citeshttps://doi.org/10.1109/icoei53556.2022.9776646openalex-snapshot
A Novel Approach to Segment OCT layers using Graph method for Glaucoma Diagnosis
inferred← citeshttps://doi.org/10.1109/mpcon66082.2025.11256552openalex-snapshot
Glaucoma Diagnosis and Progression Prediction using Deep Learning Approach
inferred← citeshttps://doi.org/10.1109/tbme.2020.3030085openalex-snapshot
Clinically Verified Hybrid Deep Learning System for Retinal Ganglion Cells Aware Grading of Glaucomatous Progression
inferred← citeshttps://doi.org/10.1142/s0219519419500659openalex-snapshot
HG-SVNN: HARMONIC GENETIC-BASED SUPPORT VECTOR NEURAL NETWORK CLASSIFIER FOR THE GLAUCOMA DETECTION
inferred← citeshttps://doi.org/10.1155/2019/9658350openalex-snapshot
Content‐Based Image Retrieval and Feature Extraction: A Comprehensive Review
inferred← citeshttps://doi.org/10.1364/optcon.497631openalex-snapshot
End-to-end algorithm for the automatic detection of the neural canal opening in OCT images based on a multi-task deep learning model
inferred← citeshttps://doi.org/10.1371/journal.pone.0203339openalex-snapshot
A Hybrid Geometric Spatial Image Representation for scene classification
inferred← citeshttps://doi.org/10.18280/ria.350407openalex-snapshot
Feature Extraction Model with Group-Based Classifier for Content Extraction from Video Data
inferred← citeshttps://doi.org/10.21015/vtse.v13i4.2232openalex-snapshot
Scalable Hybrid Deep Learning-Based Architecture for Glaucomatous and Healthy Eye Classification in Retinal Fundus Images
inferred← citeshttps://doi.org/10.22214/ijraset.2022.45227openalex-snapshot
Retinal Analysis and Calculating Cup to Disc Ratio Value Using Deep Learning Models
inferred← citeshttps://doi.org/10.22214/ijraset.2022.45811openalex-snapshot
Identical Image Extraction from PDF Document Using LBP (Local Binary Patterns) and RGB (Red, Green and Blue) Color Features
inferred← citeshttps://doi.org/10.2991/978-94-6463-136-4_71openalex-snapshot
Glaucoma Detection Through Optical Coherence Tomograph Images
inferred← citeshttps://doi.org/10.32604/iasc.2022.029850openalex-snapshot
Scale Invariant Feature Transform with Crow Optimization for Breast Cancer Detection
inferred← citeshttps://doi.org/10.3390/diagnostics14151668openalex-snapshot
Exploring Publicly Accessible Optical Coherence Tomography Datasets: A Comprehensive Overview
inferred← citeshttps://doi.org/10.3390/electronics9060909openalex-snapshot
Channel and Spatial Attention Regression Network for Cup-to-Disc Ratio Estimation
inferred← citeshttps://doi.org/10.36676/jrps.v15.i3.1520openalex-snapshot
Content-Based Image Retrieval and Feature Extraction: Analysing the Literature
inferred← citeshttps://doi.org/10.4015/s1016237224500303openalex-snapshot
INTEGRATING DUAL FUNDUS IMAGE DEEP FEATURE POOLING BASED ON CUP AND DISC SEGMENTATION FOR EFFICIENT GLAUCOMA DETECTION FRAMEWORK INDULGING HEURISTIC CONCEPT
inferred← citeshttps://doi.org/10.4018/978-1-6684-7544-7.ch073openalex-snapshot
An Artificial Intelligence-Based Smart System for Early Glaucoma Recognition Using OCT Images
inferred← citeshttps://doi.org/10.4018/ijehmc.20210701.oa3openalex-snapshot
An Artificial Intelligence-Based Smart System for Early Glaucoma Recognition Using OCT Images
inferred← citeshttps://doi.org/10.4236/ojoph.2026.162012openalex-snapshot
H-UQ-MFF: Hybrid Uncertainty-Aware Multi-Feature Fusion for Clinically-Translatable Glaucoma Detection with FDA-Compliant Validation
inferred← citeshttps://doi.org/10.47134/ijhis.v1i3.21openalex-snapshot
Glaucoma Detection Based on Texture Feature of Neuro Retinal Rim Area in Retinal Fundus Image
inferred← citeshttps://doi.org/10.5204/thesis.eprints.244729openalex-snapshot
Mathematical modeling of a light field fundus camera and its applications to retinal imaging
inferred← citeshttps://doi.org/10.59200/icarti.2023.005openalex-snapshot
Optic Disc and Vessel Segmentation in Retinal Images using Correlation Texture
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.