mlsanityData to 7 Oct 2026

OCTID: Optical Coherence Tomography Image Database

arXiv 1812.07056 ↗First posted 17 Dec 2018cs.CV cs.LGcited by 36

Not on the map. Why?

Abstract (arXiv)

Optical coherence tomography (OCT) is a non-invasive imaging modality which is widely used in clinical ophthalmology. OCT images are capable of visualizing deep retinal layers which is crucial for early diagnosis of retinal diseases. In this paper, we describe a comprehensive open-access database containing more than 500 highresolution images categorized into different pathological conditions. The image classes include Normal (NO), Macular Hole (MH), Age-related Macular Degeneration (AMD), Central Serous Retinopathy (CSR), and Diabetic Retinopathy (DR). The images were obtained from a raster scan protocol with a 2mm scan length and 512x1024 pixel resolution. We have also included 25 normal OCT images with their corresponding ground truth delineations which can be used for an accurate evaluation of OCT image segmentation. In addition, we have provided a user-friendly GUI which can be used by clinicians for manual (and semi-automated) segmentation.

Key facts. Cited by 36 papers in the map (data through 7 Oct 2026). First posted on arXiv 17 Dec 2018.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 5; 2022: 4; 2023: 2; 2024: 7; 2025: 15; 2026: 3.

36 papers.

Sort:

By area:

  1. 2023OCTDL: Optical Coherence Tomography Dataset for Image-Based Deep Learning Methodscited by 28
  2. 2025EyecareGPT: Boosting Comprehensive Ophthalmology Understanding with Tailored Dataset, Benchmark and Modelcited by 22
  3. 2022Visual Anomaly Detection Via Partition Memory Bank Module and Error Estimationcited by 20
  4. 2024EyeFound: A Multimodal Generalist Foundation Model for Ophthalmic Imagingcited by 18
  5. 2024EyeCLIP: A visual-language foundation model for multi-modal ophthalmic image analysiscited by 14
  6. 2022Dataset and Evaluation algorithm design for GOALS Challengecited by 13
  7. 2024UrFound: Towards Universal Retinal Foundation Models via Knowledge-Guided Masked Modelingcited by 10
  8. 2024MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Imagescited by 9
  9. 2021Uncertainty aware and explainable diagnosis of retinal diseasecited by 7
  10. 2025MIRAGE: Multimodal foundation model and benchmark for comprehensive retinal OCT image analysiscited by 7
  11. 2022Anomaly Detection in Retinal Images using Multi-Scale Deep Feature Sparse Codingcited by 6
  12. 2021Circumpapillary OCT-Focused Hybrid Learning for Glaucoma Grading Using Tailored Prototypical Neural Networkscited by 5
24 more
  1. 2025MM-Retinal V2: Transfer an Elite Knowledge Spark into Fundus Vision-Language Pretrainingcited by 5
  2. 2025FunBench: Benchmarking Fundus Reading Skills of MLLMscited by 5
  3. 2025Continual Retinal Vision-Language Pre-training upon Incremental Imaging Modalitiescited by 5
  4. 2025WaveNet-SF: A Hybrid Network for Retinal Disease Detection Based on Wavelet Transform in Spatial-Frequency Domaincited by 3
  5. 2025A Survey of Multimodal Ophthalmic Diagnostics: From Task-Specific Approaches to Foundational Modelscited by 3
  6. 2021Automated Detection and Diagnosis of Diabetic Retinopathy: A Comprehensive Surveycited by 2
  7. 2021Automated segmentation and extraction of posterior eye segment using OCT scanscited by 2
  8. 2021Application of Homomorphic Encryption in Medical Imagingcited by 2
  9. 2024Masked Image Modelling for retinal OCT understandingcited by 2
  10. 2024Open-Source Periorbital Segmentation Dataset for Ophthalmic Applicationscited by 2
  11. 2025Multi-Modal Explainable Medical AI Assistant for Trustworthy Human-AI Collaborationcited by 2
  12. 2022ROCT-Net: A new ensemble deep convolutional model with improved spatial resolution learning for detecting common diseases from retinal OCT imagescited by 1
  13. 2023Benchmarking of Query Strategies: Towards Future Deep Active Learningcited by 1
  14. 2025Clinician-Friendly Foundation Models for Ophthalmic Image Diagnostics without Fine-Tuning or Technical Barrierscited by 1
  15. 2025BenchReAD: A systematic benchmark for retinal anomaly detectioncited by 1
  16. 2025Randomized-MLP Regularization Improves Domain Adaptation and Interpretability in DINOv2cited by 1
  17. 2024Enhancing Diagnostic Reliability of Foundation Model with Uncertainty Estimation in OCT Imagescited by 0
  18. 2025Deep Learning for Ophthalmology: The State-of-the-Art and Future Trendscited by 0
  19. 2025PiPViT: Patch-based Visual Interpretable Prototypes for Retinal Image Analysiscited by 0
  20. 2025RetFiner: A Vision-Language Refinement Scheme for Retinal Foundation Modelscited by 0
  21. 2025EyeAgent: An Agentic AI System for Multimodal Clinical Decision Support in Ophthalmologycited by 0
  22. 2026MedKCO: Medical Vision-Language Pretraining via Knowledge-Driven Cognitive Orchestrationcited by 0
  23. 2026M-IDoL: Information Decomposition for Modality-Specific and Diverse Representation Learning in Medical Foundation Modelcited by 0
  24. 2026Representation learning from OCT imagescited by 0