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

12/01/2018
by   Meng Li, et al.
0

The change of retinal vasculature is an early sign of many vascular and systematic diseases, such as diabetes and hypertension. Different behaviors of retinal arterioles and venules form an important metric to measure the disease severity. Therefore, an accurate classification of arterioles and venules is of great necessity. In this work, we propose a novel architecture of deep convolutional neural network for segmenting and classifying arterioles and venules on retinal fundus images. This network takes the original color fundus image as inputs and multi-class labels as outputs. We adopt the encoding-decoding structure (Unet) as the backbone network of our proposed model. To improve the classification accuracy, we develop a special encoding path that couples InceptionV4 modules and Cascading Dilated Convolutions (CDCs) on top of the backbone network. The model is thus able to extract and fuse high-level semantic features from multi-scale receptive fields. The proposed method has outperformed the previous state-of-the-art method on DRIVE dataset with an accuracy of 0.955 ± 0.002.

READ FULL TEXT

page 3

page 4

research
04/11/2019

Retinal Vessels Segmentation Based on Dilated Multi-Scale Convolutional Neural Network

Accurate segmentation of retinal vessels is a basic step in Diabetic ret...
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
10/06/2021

Multi-Scale Convolutional Neural Network for Automated AMD Classification using Retinal OCT Images

Age-related macular degeneration (AMD) is the most common cause of blind...
research
07/18/2020

Multi-Task Neural Networks with Spatial Activation for Retinal Vessel Segmentation and Artery/Vein Classification

Retinal artery/vein (A/V) classification plays a critical role in the cl...
research
07/07/2017

Automatic Classification of Bright Retinal Lesions via Deep Network Features

The diabetic retinopathy is timely diagonalized through color eye fundus...
research
02/19/2022

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

Segmentation of retinal vessel images is critical to the diagnosis of re...
research
10/22/2020

Unsupervised deep learning for grading of age-related macular degeneration using retinal fundus images

Many diseases are classified based on human-defined rubrics that are pro...

Please sign up or login with your details

Forgot password? Click here to reset