DeepAI AI Chat
Log In Sign Up

Channel Attention Residual U-Net for Retinal Vessel Segmentation

by   Changlu Guo, et al.

Retinal vessel segmentation is a vital step for the diagnosis of many early eye-related diseases. In this work, we propose a new deep learning model, namely Channel Attention Residual U-Net (CAR-U-Net), to accurately segment retinal vascular and non-vascular pixels. In this model, the channel attention mechanism was introduced into Residual Block and a Channel Attention Residual Block (CARB) was proposed to enhance the discriminative ability of the network by considering the interdependence between the feature channels. Moreover, to prevent the convolutional networks from overfitting, a Structured Dropout Residual Block (SDRB) was proposed, consisting of pre-activated residual block and DropBlock. The results show that our proposed CAR-U-Net has reached the state-of-the-art performance on two publicly available retinal vessel datasets: DRIVE and CHASE DB1.


SA-UNet: Spatial Attention U-Net for Retinal Vessel Segmentation

The precise segmentation of retinal blood vessel is of great significanc...

Residual Spatial Attention Network for Retinal Vessel Segmentation

Reliable segmentation of retinal vessels can be employed as a way of mon...

U-Net with Hierarchical Bottleneck Attention for Landmark Detection in Fundus Images of the Degenerated Retina

Fundus photography has routinely been used to document the presence and ...

Segmentation of fundus vascular images based on a dual-attention mechanism

Accurately segmenting blood vessels in retinal fundus images is crucial ...

Divided We Stand: A Novel Residual Group Attention Mechanism for Medical Image Segmentation

Given that convolutional neural networks extract features via learning c...

DR-VNet: Retinal Vessel Segmentation via Dense Residual UNet

Accurate retinal vessel segmentation is an important task for many compu...

Attention W-Net: Improved Skip Connections for better Representations

Segmentation of macro and microvascular structures in fundoscopic retina...

Code Repositories