Retinal Vessel Segmentation

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

10 leaderboard tables shown for this task, 10 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

8 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

1 subtask in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

30 shown of 59 papers with code (139 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• U-Net: Convolutional Networks for Biomedical Image Segmentation
  18 May 2015 487 repositories listed Syntology ran 510 of 757 samples · 247 unverified · 426 pointer-only (licence)
  There is large consent that successful training of deep networks requires many thousand annotated training samples.
• Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net) for Medical Image Segmentation
  20 Feb 2018 12 repositories listed Syntology ran 5 of 8 samples · 3 unverified · 5 pointer-only (licence)
  In this paper, we propose a Recurrent Convolutional Neural Network (RCNN) based on U-Net as well as a Recurrent Residual Convolutional Neural Network (RRCNN) based on U-Net models, which are named RU-Net and R2U-Net…
• SA-UNet: Spatial Attention U-Net for Retinal Vessel Segmentation
  7 Apr 2020 4 repositories listed
  The precise segmentation of retinal blood vessels is of great significance for early diagnosis of eye-related diseases such as diabetes and hypertension.
• Dynamic Deep Networks for Retinal Vessel Segmentation
  19 Mar 2019 4 repositories listed
  To address this limitation, we propose a novel, stochastic training scheme for deep neural networks that better classifies the faint, ambiguous regions of the image.
• LadderNet: Multi-path networks based on U-Net for medical image segmentation
  17 Oct 2018 3 repositories listed
  A LadderNet has more paths for information flow because of skip connections and residual blocks, and can be viewed as an ensemble of Fully Convolutional Networks (FCN).
• Retinal Image Restoration and Vessel Segmentation using Modified Cycle-CBAM and CBAM-UNet
  9 Sep 2022 2 repositories listed
  The retinal vessel segmentation performance was compared with the ground-truth fundus images.
• Learning to Address Intra-segment Misclassification in Retinal Imaging
  25 Apr 2021 2 repositories listed
  Accurate multi-class segmentation is a long-standing challenge in medical imaging, especially in scenarios where classes share strong similarity.
• RV-GAN: Segmenting Retinal Vascular Structure in Fundus Photographs using a Novel Multi-scale Generative Adversarial Network
  3 Jan 2021 2 repositories listed
  In order to avoid the loss of fidelity suffered by traditional GAN-based segmentation systems, we introduce a novel weighted feature matching loss.
• The Little W-Net That Could: State-of-the-Art Retinal Vessel Segmentation with Minimalistic Models
  3 Sep 2020 2 repositories listed
  Our analysis demonstrates that the retinal vessel segmentation problem is far from solved when considering test images that differ substantially from the training data, and that this task represents an ideal scenario…
• Channel Attention Residual U-Net for Retinal Vessel Segmentation
  7 Apr 2020 2 repositories listed
  Retinal vessel segmentation is a vital step for the diagnosis of many early eye-related diseases.
• Dense Residual Network for Retinal Vessel Segmentation
  7 Apr 2020 2 repositories listed
  But for other retinal imaging modalities, more research is needed to explore vascular extraction.
• IterNet: Retinal Image Segmentation Utilizing Structural Redundancy in Vessel Networks
  12 Dec 2019 2 repositories listed
  Retinal vessel segmentation is of great interest for diagnosis of retinal vascular diseases.
• Retinal Vessel Segmentation based on Fully Convolutional Networks
  22 Nov 2019 2 repositories listed
  The morphological attributes of retinal vessels, such as length, width, tortuosity and branching pattern and angles, play an important role in diagnosis, screening, treatment, and evaluation of various cardiovascular…
• Accurate Retinal Vessel Segmentation via Octave Convolution Neural Network
  28 Jun 2019 2 repositories listed
  Compared with other convolution networks utilizing standard convolution for feature extraction, the proposed method utilizes octave convolutions and octave transposed convolutions for learning multiple-spatial-frequency…
• Retinal Vessel Segmentation in Fundoscopic Images with Generative Adversarial Networks
  28 Jun 2017 2 repositories listed
  Retinal vessel segmentation is an indispensable step for automatic detection of retinal diseases with fundoscopic images.
• Dual encoding feature filtering generalized attention UNET for retinal vessel segmentation
  2 Jun 2025 1 repository listed
  Additionally, innovative data augmentation and balancing methods are proposed to counter data scarcity and distribution imbalance, further boosting the robustness and generalization of the model.
• Novel Extraction of Discriminative Fine-Grained Feature to Improve Retinal Vessel Segmentation
  6 May 2025 1 repository listed
  AttUKAN achieves F1 scores of 82.
• A Novel Hybrid Approach for Retinal Vessel Segmentation with Dynamic Long-Range Dependency and Multi-Scale Retinal Edge Fusion Enhancement
  18 Apr 2025 1 repository listed
  Accurate retinal vessel segmentation provides essential structural information for ophthalmic image analysis.
• Full-scale Representation Guided Network for Retinal Vessel Segmentation
  31 Jan 2025 1 repository listed
  Passing full-scale information to the attention block allows for the generation of improved attention maps, which are then passed to the attention-guided filter, resulting in performance enhancement of the segmentation…
• Topology-aware Mamba for Crack Segmentation in Structures
  25 Oct 2024 1 repository listed
  CrackMamba, a Mamba-based model, is designed for efficient and accurate crack segmentation for monitoring the structural health of infrastructure.
• AdaptDiff: Cross-Modality Domain Adaptation via Weak Conditional Semantic Diffusion for Retinal Vessel Segmentation
  6 Oct 2024 1 repository listed
  Subsequently, we sample on the target domain with binary vessel masks from the source domain to get paired data, i.
• Pediatric Wrist Fracture Detection Using Feature Context Excitation Modules in X-ray Images
  1 Oct 2024 1 repository listed
  Children often suffer wrist trauma in daily life, while they usually need radiologists to analyze and interpret X-ray images before surgical treatment by surgeons.
• VascX Models: Model Ensembles for Retinal Vascular Analysis from Color Fundus Images
  24 Sep 2024 1 repository listed
  Additional CFIs, mainly from the population-based Rotterdam Study were annotated by graders for arteries and veins at pixel level, resulting in a dataset diverse in patient demographics and imaging conditions.
• Conformal Performance Range Prediction for Segmentation Output Quality Control
  18 Jul 2024 1 repository listed Syntology ran 2 of 3 samples · 1 unverified · 3 pointer-only (licence)
  Our results show that it is possible to achieve the desired coverage with small prediction ranges, highlighting the potential of performance range prediction as a valuable tool for output quality control.
• Image-level Regression for Uncertainty-aware Retinal Image Segmentation
  27 May 2024 1 repository listed
  Accurate retinal vessel (RV) segmentation is a crucial step in the quantitative assessment of retinal vasculature, which is needed for the early detection of retinal diseases and other conditions.
• Enhancing Retinal Vascular Structure Segmentation in Images With a Novel Design Two-Path Interactive Fusion Module Model
  3 Mar 2024 1 repository listed
  Precision in identifying and differentiating micro and macro blood vessels in the retina is crucial for the diagnosis of retinal diseases, although it poses a significant challenge.
• G-CASCADE: Efficient Cascaded Graph Convolutional Decoding for 2D Medical Image Segmentation
  24 Oct 2023 1 repository listed Syntology ran 6 of 9 samples · 3 unverified · 9 pointer-only (licence)
  The encoder utilizes the self-attention mechanism to capture long-range dependencies, while the decoder refines the feature maps preserving long-range information due to the global receptive fields of the graph…
• RSF-Conv: Rotation-and-Scale Equivariant Fourier Parameterized Convolution for Retinal Vessel Segmentation
  27 Sep 2023 1 repository listed
  Retinal vessel segmentation is of great clinical significance for the diagnosis of many eye-related diseases, but it is still a formidable challenge due to the intricate vascular morphology.
• An Accurate and Efficient Neural Network for OCTA Vessel Segmentation and a New Dataset
  18 Sep 2023 1 repository listed
  Optical coherence tomography angiography (OCTA) is a noninvasive imaging technique that can reveal high-resolution retinal vessels.
• LUNet: Deep Learning for the Segmentation of Arterioles and Venules in High Resolution Fundus Images
  11 Sep 2023 1 repository listed
  Using active learning, we created a new DFI dataset containing 240 crowd-sourced manual A/V segmentations performed by fifteen medical students and reviewed by an ophthalmologist, and developed LUNet, a novel deep…

Syntology lines on 4 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.