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Retinal Vessel Segmentation
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Retinal vessel segmentation is the task of segmenting vessels in retina imagery.
<span style="color:grey; opacity: 0.6">( Image credit: LadderNet )</span>
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Objective-Dependent Uncertainty Driven Retinal Vessel Segmentation
Pyramid U-Net for Retinal Vessel Segmentation
Contextual Information Enhanced Convolutional Neural Networks for Retinal Vessel Segmentation in Color Fundus Images
Study Group Learning: Improving Retinal Vessel Segmentation Trained with Noisy Labels
RV-GAN: Segmenting Retinal Vascular Structure in Fundus Photographs using a Novel Multi-scale Generative Adversarial Network
The Unreasonable Effectiveness of Encoder-Decoder Networks for Retinal Vessel Segmentation
Genetic U-Net: Automatically Designed Deep Networks for Retinal Vessel Segmentation Using a Genetic Algorithm
Residual Spatial Attention Network for Retinal Vessel Segmentation
The Little W-Net That Could: State-of-the-Art Retinal Vessel Segmentation with Minimalistic Models
NuI-Go: Recursive Non-Local Encoder-Decoder Network for Retinal Image Non-Uniform Illumination Removal
Robust Retinal Vessel Segmentation from a Data Augmentation Perspective
Multi-Task Neural Networks with Spatial Activation for Retinal Vessel Segmentation and Artery/Vein Classification
ROSE: A Retinal OCT-Angiography Vessel Segmentation Dataset and New Model
An Elastic Interaction-Based Loss Function for Medical Image Segmentation
Modeling and Enhancing Low-quality Retinal Fundus Images
Retinal vessel segmentation by probing adaptive to lighting variations
Boosting Connectivity in Retinal Vessel Segmentation via a Recursive Semantics-Guided Network
Extreme Consistency: Overcoming Annotation Scarcity and Domain Shifts
SA-UNet: Spatial Attention U-Net for Retinal Vessel Segmentation
Dense Residual Network for Retinal Vessel Segmentation
Channel Attention Residual U-Net for Retinal Vessel Segmentation
Evolutionary Neural Architecture Search for Retinal Vessel Segmentation
A Two-Stream Meticulous Processing Network for Retinal Vessel Segmentation
Patch-based Generative Adversarial Network Towards Retinal Vessel Segmentation
IterNet: Retinal Image Segmentation Utilizing Structural Redundancy in Vessel Networks
Retinal Vessel Segmentation based on Fully Convolutional Networks
HybridNetSeg: A Compact Hybrid Network for Retinal Vessel Segmentation
What Do We Really Need? Degenerating U-Net on Retinal Vessel Segmentation
Lesson Learnt: Modularization of Deep Networks Allow Cross-Modality Reuse
Penalizing small errors using an Adaptive Logarithmic Loss
ErrorNet: Learning error representations from limited data to improve vascular segmentation
A Refined Equilibrium Generative Adversarial Network for Retinal Vessel Segmentation
Bi-Directional ConvLSTM U-Net with Densley Connected Convolutions
Automated retinal vessel segmentation based on morphological preprocessing and 2D-Gabor wavelets
A Two Stage GAN for High Resolution Retinal Image Generation and Segmentation
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