SPNet: A novel deep neural network for retinal vessel segmentation based on shared decoder and pyramid-like loss

02/19/2022
by   Geng-Xin Xu, et al.
0

Segmentation of retinal vessel images is critical to the diagnosis of retinopathy. Recently, convolutional neural networks have shown significant ability to extract the blood vessel structure. However, it remains challenging to refined segmentation for the capillaries and the edges of retinal vessels due to thickness inconsistencies and blurry boundaries. In this paper, we propose a novel deep neural network for retinal vessel segmentation based on shared decoder and pyramid-like loss (SPNet) to address the above problems. Specifically, we introduce a decoder-sharing mechanism to capture multi-scale semantic information, where feature maps at diverse scales are decoded through a sequence of weight-sharing decoder modules. Also, to strengthen characterization on the capillaries and the edges of blood vessels, we define a residual pyramid architecture which decomposes the spatial information in the decoding phase. A pyramid-like loss function is designed to compensate possible segmentation errors progressively. Experimental results on public benchmarks show that the proposed method outperforms the backbone network and the state-of-the-art methods, especially in the regions of the capillaries and the vessel contours. In addition, performances on cross-datasets verify that SPNet shows stronger generalization ability.

READ FULL TEXT

page 2

page 10

page 18

research
04/06/2021

Pyramid U-Net for Retinal Vessel Segmentation

Retinal blood vessel can assist doctors in diagnosis of eye-related dise...
research
10/09/2020

Rethinking the Extraction and Interaction of Multi-Scale Features for Vessel Segmentation

Analyzing the morphological attributes of blood vessels plays a critical...
research
03/25/2021

Contextual Information Enhanced Convolutional Neural Networks for Retinal Vessel Segmentation in Color Fundus Images

Accurate retinal vessel segmentation is a challenging problem in color f...
research
06/24/2018

Scale Space Approximation in Convolutional Neural Networks for Retinal Vessel Segmentation

Retinal images have the highest resolution and clarity among medical ima...
research
07/30/2021

Topological Similarity Index and Loss Function for Blood Vessel Segmentation

Blood vessel segmentation is one of the most studied topics in computer ...
research
01/18/2019

Feature Pyramid and Hierarchical Boosting Network for Pavement Crack Detection

Pavement crack detection is a critical task for insuring road safety. Ma...
research
12/01/2018

Automated segmentaiton and classification of arterioles and venules using Cascading Dilated Convolutional Neural Networks

The change of retinal vasculature is an early sign of many vascular and ...

Please sign up or login with your details

Forgot password? Click here to reset