期刊论文

Jiao, Ge(jiaoge@126.com)

英文

工程与科学中的计算机建模(英文)

1526-1492

2023

136

3

2465-2485

10.32604/cmes.2023.026189

Funding Statement: This work is supported by the Hunan Provincial Natural Science Foundation of China (2021JJ50074), the Scientific Research Fund of Hunan Provincial Education Department (19B082), the Science and Technology Development Center of the Ministry of Education-New Generation Information Technology Innovation Project (2018A02020), the Science Foundation of Hengyang Normal University (19QD12), the Science and Technology Plan Project of Hunan Province (2016TP1020), the Subject Group Construction Project of Hengyang Normal University (18XKQ02), the Application Oriented Special Disciplines, Double First Class University Project of Hunan Province (Xiangjiaotong [2018] 469), the Hunan Province Special Funds of Central Government for Guiding Local Science and Technology Development (2018CT5001), the First Class Undergraduate Major in Hunan Province Internet of Things Major (Xiangjiaotong [2020] 248, No. 288).

本校为第一机构

The accurate and automatic segmentation of retinal vessels from fundus images is critical for the early diagnosis and prevention of many eye diseases, such as diabetic retinopathy (DR). Existing retinal vessel segmentation approaches based on convolutional neural networks (CNNs) have achieved remarkable effectiveness. Here, we extend a retinal vessel segmentation model with low complexity and high performance based on U-Net, which is one of the most popular architectures. In view of the excellent work of depth-wise separable convolution, we int...