计算机科学与探索2024，Vol.18Issue(8)：1960-1978,19.DOI:10.3778/j.issn.1673-9418.2310083
深度学习的视网膜血管分割研究综述
Review of Research on Deep Learning in Retinal Blood Vessel Segmentation
摘要
Abstract
The segmentation results of retinal fundus images can provide auxiliary diagnosis for ophthalmic diseases such as diabetic retinopathy,glaucoma,and age-related macular degeneration.Accurate segmentation of retinal blood vessels provides strong support for diagnosis,treatment,and evaluation,helping doctors better understand the patient's eye condition.This paper reviews recent papers on fundus vessel segmentation based on deep learning,introducing the most commonly used datasets for fundus vessel segmentation and preprocessing methods.It also classifies recent model algorithms into several categories:single-network models,multi-network models,and Trans-former models.This paper introduces various modules within each category of networks,discussing their advantages and limitations in handling fundus vessel segmentation tasks.These analyses help us understand the characteristics and applicable scenarios of different modules.Furthermore,this paper summarizes the retrieved model data,compar-ing the performance of different algorithms on the same dataset and evaluating their strengths and weaknesses based on scores obtained from the same evaluation metrics.It analyzes the reasons for the advantages of better-scoring algorithms and points out the defects of current algorithms.Finally,it summarizes numerous challenges faced by deep learning methods in retinal vessel segmentation and identifies potential directions for future development of deep learning in fundus vessel segmentation.关键词
眼底图像/血管分割/深度学习Key words
fundus images/blood vessel segmentation/deep learning分类
信息技术与安全科学引用本文复制引用
汪有崧,裴峻鹏,李增辉,王伟..深度学习的视网膜血管分割研究综述[J].计算机科学与探索,2024,18(8):1960-1978,19.基金项目
国家部委基金. This work was supported by the Foundation of China Ministries and Commissions. （）
