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ReLayNet: Retinal Layer and Fluid Segmentation of Macular Optical Coherence Tomography using Fully Convolutional Network

arXiv 1704.02161 ↗First posted 7 Apr 2017cs.CVcited by 37

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Abstract (arXiv)

Optical coherence tomography (OCT) is used for non-invasive diagnosis of diabetic macular edema assessing the retinal layers. In this paper, we propose a new fully convolutional deep architecture, termed ReLayNet, for end-to-end segmentation of retinal layers and fluid masses in eye OCT scans. ReLayNet uses a contracting path of convolutional blocks (encoders) to learn a hierarchy of contextual features, followed by an expansive path of convolutional blocks (decoders) for semantic segmentation. ReLayNet is trained to optimize a joint loss function comprising of weighted logistic regression and Dice overlap loss. The framework is validated on a publicly available benchmark dataset with comparisons against five state-of-the-art segmentation methods including two deep learning based approaches to substantiate its effectiveness.

Key facts. Cited by 37 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 Apr 2017.

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Citing papers per year: 2021: 4; 2022: 11; 2023: 5; 2024: 4; 2025: 8; 2026: 5.

37 papers.

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  1. 2021Uncertainty guided semi-supervised segmentation of retinal layers in OCT imagescited by 29
  2. 2022Y-Net: A Spatiospectral Dual-Encoder Networkfor Medical Image Segmentationcited by 19
  3. 2022SD-LayerNet: Semi-supervised retinal layer segmentation in OCT using disentangled representation with anatomical priorscited by 7
  4. 2023Simultaneous Alignment and Surface Regression Using Hybrid 2D-3D Networks for 3D Coherent Layer Segmentation of Retinal OCT Images with Full and Sparse Annotationscited by 7
  5. 2025MIRAGE: Multimodal foundation model and benchmark for comprehensive retinal OCT image analysiscited by 7
  6. 2022RetiFluidNet: A Self-Adaptive and Multi-Attention Deep Convolutional Network for Retinal OCT Fluid Segmentationcited by 6
  7. 2022Segmentation-guided Domain Adaptation and Data Harmonization of Multi-device Retinal Optical Coherence Tomography using Cycle-Consistent Generative Adversarial Networkscited by 5
  8. 2022Segmentation of Bruch's Membrane in retinal OCT with AMD using anatomical priors and uncertainty quantificationcited by 5
  9. 2022Simultaneous Alignment and Surface Regression Using Hybrid 2D-3D Networks for 3D Coherent Layer Segmentation of Retina OCT Imagescited by 3
  10. 2023Robotic Navigation Autonomy for Subretinal Injection via Intelligent Real-Time Virtual iOCT Volume Slicingcited by 3
  11. 2023Retinal Image Segmentation with Small Datasetscited by 3
  12. 2024Light-weight Retinal Layer Segmentation with Global Reasoningcited by 3
25 more
  1. 2022FourierNet: Shape-Preserving Network for Henle's Fiber Layer Segmentation in Optical Coherence Tomography Imagescited by 2
  2. 2022A deep learning network with differentiable dynamic programming for retina OCT surface segmentationcited by 2
  3. 2025SD-RetinaNet: Topologically Constrained Semi-Supervised Retinal Lesion and Layer Segmentation in OCTcited by 2
  4. 2021Corneal Pachymetry by AS-OCT after Descemet's Membrane Endothelial Keratoplastycited by 1
  5. 2021Automatic Segmentation of the Optic Nerve Head Region in Optical Coherence Tomography: A Methodological Reviewcited by 1
  6. 2023nnUNet RASPP for Retinal OCT Fluid Detection, Segmentation and Generalisation over Variations of Data Sourcescited by 1
  7. 2024Formula-Driven Data Augmentation and Partial Retinal Layer Copying for Retinal Layer Segmentationcited by 1
  8. 2025Deep Learning for Retinal Degeneration Assessment: A Comprehensive Analysis of the MARIO Challengecited by 1
  9. 2025Universal Wavelet Units in 3D Retinal Layer Segmentationcited by 1
  10. 2026Multi-Scale Global-Instance Prompt Tuning for Continual Test-time Adaptation in Medical Image Segmentationcited by 1
  11. 2021ReLaX: Retinal Layer Attribution for Guided Explanations of Automated Optical Coherence Tomography Classificationcited by 0
  12. 2022A generalizable approach based on U-Net model for automatic Intra retinal cyst segmentation in SD-OCT imagescited by 0
  13. 2022Superresolution and Segmentation of OCT scans using Multi-Stage adversarial Guided Attention Trainingcited by 0
  14. 2022GAN-based Super-Resolution and Segmentation of Retinal Layers in Optical coherence tomography Scanscited by 0
  15. 2023SwinVFTR: A Novel Volumetric Feature-learning Transformer for 3D OCT Fluid Segmentationcited by 0
  16. 2024Innovative Quantitative Analysis for Disease Progression Assessment in Familial Cerebral Cavernous Malformationscited by 0
  17. 2024SpecstatOR: Speckle statistics-based iOCT Segmentation Network for Ophthalmic Surgerycited by 0
  18. 2025Comprehensive Evaluation of OCT-based Automated Segmentation of Retinal Layer, Fluid and Hyper-Reflective Foci: Impact on Clinical Assessment of Diabetic Retinopathy Severitycited by 0
  19. 2025Attentional Triple-Encoder Network in Spatiospectral Domains for Medical Image Segmentationcited by 0
  20. 2025Adaptive Confidence-Wise Loss for Improved Lens Structure Segmentation in AS-OCTcited by 0
  21. 2025RiverScope: High-Resolution River Masking Datasetcited by 0
  22. 2026Retinal Layer Segmentation in OCT Images With 2.5D Cross-slice Feature Fusion Module for Glaucoma Assessmentcited by 0
  23. 2026TAPE: A two-stage parameter-efficient adaptation framework for foundation models in OCT-OCTA analysiscited by 0
  24. 2026SAIL: Structure-Aware Interpretable Learning for Anatomy-Aligned Post-hoc Explanations in OCTcited by 0
  25. 2026PC-Seg: Progressive Cross-View Consistency for 3D OCT Segmentation from Sparse 2D Annotationscited by 0