Retinal Vessel Segmentation Edit Task
Medical • Medical Image Segmentation
About
Retinal vessel segmentation is the task of segmenting vessels in retina imagery.
( Image credit: LadderNet )
Benchmarks
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Greatest papers with code
U-Net: Convolutional Networks for Biomedical Image Segmentation
There is large consent that successful training of deep networks requires many thousand annotated training samples.
Ranked #1 on
Cell Segmentation
on DIC-HeLa
CELL SEGMENTATION COLORECTAL GLAND SEGMENTATION: ELECTRON MICROSCOPY IMAGE SEGMENTATION IMAGE AUGMENTATION LESION SEGMENTATION LUNG NODULE SEGMENTATION MULTI-TISSUE NUCLEUS SEGMENTATION RETINAL VESSEL SEGMENTATION SEMANTIC SEGMENTATION SKIN CANCER SEGMENTATION
Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net) for Medical Image Segmentation
• LeeJunHyun/Image_Segmentation
• 
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 respectively.
IMAGE CLASSIFICATION LESION SEGMENTATION LUNG NODULE SEGMENTATION RETINAL VESSEL SEGMENTATION SEMANTIC SEGMENTATION SKIN CANCER SEGMENTATION
Robust Retinal Vessel Segmentation from a Data Augmentation Perspective
In this paper, we propose two new data augmentation modules, namely, channel-wise random Gamma correction and channel-wise random vessel augmentation.
Retinal Vessel Segmentation in Fundoscopic Images with Generative Adversarial Networks
• ChengBinJin/V-GAN-tensorflow
• 
Retinal vessel segmentation is an indispensable step for automatic detection of retinal diseases with fundoscopic images.
Accurate Retinal Vessel Segmentation via Octave Convolution Neural Network
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 features, thus can better capture retinal vasculatures with varying sizes and shapes.
LadderNet: Multi-path networks based on U-Net for medical image segmentation
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).
Ranked #3 on
Retinal Vessel Segmentation
on CHASE_DB1
Road Extraction by Deep Residual U-Net
Road extraction from aerial images has been a hot research topic in the field of remote sensing image analysis.
Ranked #2 on
Lung Nodule Segmentation
on LUNA
LESION SEGMENTATION LUNG NODULE SEGMENTATION RETINAL VESSEL SEGMENTATION SEMANTIC SEGMENTATION SKIN CANCER SEGMENTATION
IterNet: Retinal Image Segmentation Utilizing Structural Redundancy in Vessel Networks
Retinal vessel segmentation is of great interest for diagnosis of retinal vascular diseases.
Ranked #2 on
Retinal Vessel Segmentation
on CHASE_DB1
Residual Spatial Attention Network for Retinal Vessel Segmentation
• clguo/RSAN
•
In this work, we propose the Residual Spatial Attention Network (RSAN) for retinal vessel segmentation.
Deep Vessel Segmentation By Learning Graphical Connectivity
• syshin1014/VGN
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We propose a novel deep-learning-based system for vessel segmentation.
Ranked #1 on
Retinal Vessel Segmentation
on HRF