SOTAVerified

Retinal Vessel Segmentation

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

( Image credit: LadderNet )

Papers

Showing 101–125 of 139 papers

TitleStatusHype
Resolution-Aware Design of Atrous Rates for Semantic Segmentation Networks—0
Connection Sensitive Attention U-NET for Accurate Retinal Vessel Segmentation—0
Retinal Vessel Segmentation Based on Conditional Deep Convolutional Generative Adversarial Networks—0
Boosting Connectivity in Retinal Vessel Segmentation via a Recursive Semantics-Guided Network—0
Blindness (Diabetic Retinopathy) Severity Scale Detection—0
Retinal vessel segmentation by probing adaptive to lighting variations—0
A Divide-and-Conquer Approach towards Understanding Deep Networks—0
Retinal Vessel Segmentation under Extreme Low Annotation: A Generative Adversarial Network Approach—0
Retinal Vessel Segmentation Using A New Topological Method—0
Retinal Vessel Segmentation via a Multi-resolution Contextual Network and Adversarial Learning—0
Retinal Vessel Segmentation via Neuron Programming—0
Retinal Vessel Segmentation with Deep Graph and Capsule Reasoning—0
Automated retinal vessel segmentation based on morphological preprocessing and 2D-Gabor wavelets—0
VesselMorph: Domain-Generalized Retinal Vessel Segmentation via Shape-Aware Representation—0
Robust Retinal Vessel Segmentation from a Data Augmentation Perspective—0
A Two-Stream Meticulous Processing Network for Retinal Vessel Segmentation—0
RVD: A Handheld Device-Based Fundus Video Dataset for Retinal Vessel Segmentation—0
A Two Stage GAN for High Resolution Retinal Image Generation and Segmentation—0
Attention W-Net: Improved Skip Connections for better Representations—0
Scale Space Approximation in Convolutional Neural Networks for Retinal Vessel Segmentation—0
SCOPE: Structural Continuity Preservation for Medical Image Segmentation—0
A Trio-Method for Retinal Vessel Segmentation using Image Processing—0
Serp-Mamba: Advancing High-Resolution Retinal Vessel Segmentation with Selective State-Space Model—0
Deep supervision with additional labels for retinal vessel segmentation task—0
DGSSA: Domain generalization with structural and stylistic augmentation for retinal vessel segmentation—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