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App. Res. of Comp. Accepted Paper
Vol. 42, 2025 No. 5

Research progress in retinal vessel segmentation based on deep learning

Zhang Wenhao
Qu Shaojun
Yan Meili
College of Information Science & Engineering, Hunan Normal University, Changsha 410081
DOI: 10.19734/j.issn.1001-3695.2024.07.0342

Abstract

As an important part of semantic segmentation related to human health, medical image segmentation has always been highly concerned and valued. Among them, retinal vessel segmentation is to segment and extract vascular pixels from retinal images in the fundus, which can help doctors quickly diagnose eye diseases. However, the morphology of retinal blood vessels is complex and the structure is small, making segmentation difficult. With the continuous development of research in the field of deep learning, the continuous advancement of technology has greatly improved the accuracy of image segmentation. To better understand the development of retinal vessel segmentation methods, this article comprehensively summarizes the research results of deep learning-based retinal vessel segmentation in recent years. Firstly, it introduces the commonly used datasets for retinal vessel segmentation, and discusses the key evaluation indicators and loss function. Then classify and summarize the results according to methods based on network structure design (such as U-shaped network variants) , module design (such as attention modules) , generative adversarial learning, and Transformer, analyze the advantages and disadvantages of each method, and compare the performance of the models. Finally, discussing the corresponding solutions and ideas for several major problems and challenges in retinal vessel segmentation, and providing prospects for future development to promote retinal vessel segmentation technology's progress further has good reference value.

Foundation Support

国家自然科学基金资助项目(12071126)
湖南省教育厅科学研究重点资助项目(23A0081)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.07.0342
Publish at: Application Research of Computers Accepted Paper, Vol. 42, 2025 No. 5

Publish History

[2025-03-06] Accepted Paper

Cite This Article

张文豪, 瞿绍军, 颜美丽. 基于深度学习的视网膜血管分割研究进展 [J]. 计算机应用研究, 2025, 42 (5). (2025-03-06). https://doi.org/10.19734/j.issn.1001-3695.2024.07.0342. (Zhang Wenhao, Qu Shaojun, Yan Meili. Research progress in retinal vessel segmentation based on deep learning [J]. Application Research of Computers, 2025, 42 (5). (2025-03-06). https://doi.org/10.19734/j.issn.1001-3695.2024.07.0342. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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