计算机科学与探索2025，Vol.19Issue(11)：2935-2949,15.DOI:10.3778/j.issn.1673-9418.2412031
U-Net及其变体在视网膜血管自动分割中的应用研究
Research on Application of U-Net and Its Variants in Automatic Segmentation of Retinal Vessels
摘要
Abstract
Research on retinal vessel segmentation aims to facilitate the early diagnosis and pathological analysis of fundus diseases,providing crucial support for doctors to assess patients'ocular health.The rapid advancement of deep learning technologies has introduced novel approaches and breakthroughs in the segmentation performance of retinal vessel images.Among these,U-Net has emerged as a mainstream segmentation model in this field due to its outstanding performance.This paper comprehensively reviews recent progress in the application of U-Net and its improved models in retinal vessel segmentation.It firstly introduces commonly used datasets and evaluation metrics for retinal vessel segmentation,then gives an overview of the U-Net model and its primary structural enhancement strategies.Furthermore,the paper categorizes U-Net variants into single-network models and multi-network models.From the perspective of single-network models,it elaborates on improvements such as attention mechanisms,residual structures,multi-scale feature modules,and convolutional modules.For multi-network models,it examines enhancements like cascaded U-Net,dual-path U-Net,the integration of generative adversarial networks(GANs),and the incorporation of Transformer and Mamba models.A comparative analysis is conducted to summarize the improvements and limitations of various studies in terms of model architecture,feature extraction,performance optimization,and experimental results on public datasets.Based on this analysis,the paper discusses current challenges and future prospects in the field.关键词
视网膜血管分割/U-Net/深度学习/图像处理Key words
retinal vessel segmentation/U-Net/deep learning/image processing分类
计算机与自动化引用本文复制引用
刘艳艳,董彦如,张凯,王晓燕,王旭..U-Net及其变体在视网膜血管自动分割中的应用研究[J].计算机科学与探索,2025,19(11):2935-2949,15.基金项目
山东省研究生优质教育教学资源项目(2024k147) （2024k147）
山东省研究生教育教学改革研究项目(2024G137) （2024G137）
山东省中医药科技项目(2021M146) （2021M146）
山东中医药大学科学研究基金(KYZK2024M13). This work was supported by the Shandong Province Graduate Education High-Quality Teaching Resources Project(2024k147),the Shandong Province Graduate Education Teaching Reform Research Project(2024G137),the Shandong Province Traditional Chinese Medicine Science and Technology Project(2021M146),and the Scientific Research Fund Project of Shandong University of Traditional Chinese Medicine(KYZK2024M13). （KYZK2024M13）
