SOTAVerified

Retinal Vessel Segmentation

Retinal vessel segmentation is the task of segmenting vessels in retina imagery.

( Image credit: LadderNet )

Papers

Showing 51–100 of 139 papers

TitleStatusHype
LadderNet: Multi-path networks based on U-Net for medical image segmentationCode0
LUNet: Deep Learning for the Segmentation of Arterioles and Venules in High Resolution Fundus ImagesCode0
Novel Extraction of Discriminative Fine-Grained Feature to Improve Retinal Vessel SegmentationCode0
Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net) for Medical Image SegmentationCode0
Retinal Vessel Segmentation in Fundoscopic Images with Generative Adversarial NetworksCode0
Exploring Generalizable Distillation for Efficient Medical Image SegmentationCode0
Student Becomes Decathlon Master in Retinal Vessel Segmentation via Dual-teacher Multi-target Domain AdaptationCode0
The Unreasonable Effectiveness of Encoder-Decoder Networks for Retinal Vessel SegmentationCode0
A publicly available vessel segmentation algorithm for SLO images—0
FS-Net: Full Scale Network and Adaptive Threshold for Improving Extraction of Micro-Retinal Vessel Structures—0
Deep learning-based retinal vessel segmentation with cross-modal evaluation—0
Deep Dilated Convolutional Nets for the Automatic Segmentation of Retinal Vessels—0
Deep Angiogram: Trivializing Retinal Vessel Segmentation—0
Genetic U-Net: Automatically Designed Deep Networks for Retinal Vessel Segmentation Using a Genetic Algorithm—0
GrInAdapt: Scaling Retinal Vessel Structural Map Segmentation Through Grounding, Integrating and Adapting Multi-device, Multi-site, and Multi-modal Fundus Domains—0
HybridNetSeg: A Compact Hybrid Network for Retinal Vessel Segmentation—0
_1DecNet+: A new architecture framework by _1 decomposition and iteration unfolding for sparse feature segmentation—0
TransUNext: towards a more advanced U-shaped framework for automatic vessel segmentation in the fundus image—0
Image Magnification Network for Vessel Segmentation in OCTA Images—0
Impact of loss function in Deep Learning methods for accurate retinal vessel segmentation—0
Ant Colony based Feature Selection Heuristics for Retinal Vessel Segmentation—0
KLDD: Kalman Filter based Linear Deformable Diffusion Model in Retinal Image Segmentation—0
A Novel Retinal Vessel Segmentation Based On Histogram Transformation Using 2-D Morlet Wavelet and Supervised Classification—0
DASA: Domain Adaptation in Stacked Autoencoders using Systematic Dropout—0
Lesson Learnt: Modularization of Deep Networks Allow Cross-Modality Reuse—0
LIFE: A Generalizable Autodidactic Pipeline for 3D OCT-A Vessel Segmentation—0
Low complexity convolutional neural network for vessel segmentation in portable retinal diagnostic devices—0
Universal Vessel Segmentation for Multi-Modality Retinal Images—0
M2U-Net: Effective and Efficient Retinal Vessel Segmentation for Resource-Constrained Environments—0
MDFI-Net: Multiscale Differential Feature Interaction Network for Accurate Retinal Vessel Segmentation—0
(M)SLAe-Net: Multi-Scale Multi-Level Attention embedded Network for Retinal Vessel Segmentation—0
Multi-Task Neural Networks with Spatial Activation for Retinal Vessel Segmentation and Artery/Vein Classification—0
A Fully Convolutional Neural Network based Structured Prediction Approach Towards the Retinal Vessel Segmentation—0
NuI-Go: Recursive Non-Local Encoder-Decoder Network for Retinal Image Non-Uniform Illumination Removal—0
Objective-Dependent Uncertainty Driven Retinal Vessel Segmentation—0
DA-Net: A Disentangled and Adaptive Network for Multi-Source Cross-Lingual Transfer Learning—0
Orientation and Context Entangled Network for Retinal Vessel Segmentation—0
Overview of Deep Learning Methods for Retinal Vessel Segmentation—0
PAENet: A Progressive Attention-Enhanced Network for 3D to 2D Retinal Vessel Segmentation—0
Parametric Scaling of Preprocessing assisted U-net Architecture for Improvised Retinal Vessel Segmentation—0
Particle Swarm Optimization for Great Enhancement in Semi-Supervised Retinal Vessel Segmentation with Generative Adversarial Networks—0
Patch-based Generative Adversarial Network Towards Retinal Vessel Segmentation—0
Penalizing small errors using an Adaptive Logarithmic Loss—0
Convolutional Prompting for Broad-Domain Retinal Vessel Segmentation—0
PixelBNN: Augmenting the PixelCNN with batch normalization and the presentation of a fast architecture for retinal vessel segmentation—0
Pyramid U-Net for Retinal Vessel Segmentation—0
RC-Net: A Convolutional Neural Network for Retinal Vessel Segmentation—0
Unsupervised Domain Adaptation for Retinal Vessel Segmentation with Adversarial Learning and Transfer Normalization—0
Region Guided Attention Network for Retinal Vessel Segmentation—0
Contextual Information Enhanced Convolutional Neural Networks for Retinal Vessel Segmentation in Color Fundus Images—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Swin-Res-NetAUC0.99—Unverified
2FR-UNetAUC0.99—Unverified
3Study Group LearningAUC0.99—Unverified
4SA-UNetAUC0.99—Unverified
5DEFFA-UnetAUC0.99—Unverified
6U-NetAUC0.99—Unverified
7DA-NetAUC0.98—Unverified
8FSG-NetAUC0.98—Unverified
9IterNetAUC0.98—Unverified
10VGNAUC0.98—Unverified
#ModelMetricClaimedVerifiedStatus
1FSG-NetAUC0.99—Unverified
2Study Group LearningAUC0.99—Unverified
3RV-GANAUC0.99—Unverified
4FR-UNetAUC0.99—Unverified
5SA-UNetAUC0.99—Unverified
6IterNetAUC0.99—Unverified
7LadderNetAUC0.98—Unverified
8VGNAUC0.98—Unverified
9DEFFA-UnetAUC0.98—Unverified
10R2U-NetAUC0.98—Unverified
#ModelMetricClaimedVerifiedStatus
1DA-NetAUC0.99—Unverified
2R2U-NetAUC0.99—Unverified
3FSG-NetAUC0.99—Unverified
4RV-GANAUC0.99—Unverified
5VGNAUC0.99—Unverified
6DEFFA-UnetAUC0.98—Unverified
7DUNetAUC0.98—Unverified
8U-Net ASPPmIOU0.9—Unverified
9Residual U-NetF1 score0.84—Unverified
#ModelMetricClaimedVerifiedStatus
1OCTA-NetDice Score70.74—Unverified
2U-NetDice Score66.05—Unverified
3ResU-NetDice Score65.67—Unverified
4OCTAve: OCTA-NetDice Score62.55—Unverified
5CE-NetDice Score57.83—Unverified
#ModelMetricClaimedVerifiedStatus
1OCTAve: OCTA-NetDice Score78.03—Unverified
2OCTA-NetDice Score76.97—Unverified
3CE-NetDice Score75.11—Unverified
4ResU-NetDice Score74.61—Unverified
5U-NetDice Score71.16—Unverified
#ModelMetricClaimedVerifiedStatus
1OCTAve: OCTA-NetDice Score81.42—Unverified
2OCTA-NetDice Score75.76—Unverified
3ResU-NetDice Score74.61—Unverified
4CE-NetDice Score73—Unverified
5U-NetDice Score70.12—Unverified
#ModelMetricClaimedVerifiedStatus
1OCTAve: OCTA-NetDice Score71.18—Unverified
2OCTA-NetDice Score70.77—Unverified
3CE-NetDice Score70.66—Unverified
4ResU-NetDice Score67.25—Unverified
5U-NetDice Score65.64—Unverified
#ModelMetricClaimedVerifiedStatus
1LUNetAverage Dice (0.5*Dice_a + 0.5*Dice_v)83.2—Unverified
2Junior OphtalmologistAverage Dice (0.5*Dice_a + 0.5*Dice_v)82.6—Unverified
3VascXAverage Dice (0.5*Dice_a + 0.5*Dice_v)80.6—Unverified
4AutomorphAverage Dice (0.5*Dice_a + 0.5*Dice_v)74—Unverified
5Little W-NetAverage Dice (0.5*Dice_a + 0.5*Dice_v)60.9—Unverified
#ModelMetricClaimedVerifiedStatus
1FSG-NetAUC0.99—Unverified
2DEFFA-UnetAUC0.98—Unverified
3VGNAUC0.98—Unverified
4U-Net ASPPmIoU0.9—Unverified
#ModelMetricClaimedVerifiedStatus
1LUNetAverage Dice75.6—Unverified