RetinalVasNet: a deep learning approach for robust retinal microvasculature detection.

IF 3.9 3区生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY

Frontiers in Molecular Biosciences Pub Date : 2025-08-14 eCollection Date: 2025-01-01 DOI:10.3389/fmolb.2025.1562608

Zhaomin Yao, Cengcong Xing, Gancheng Zhu, Weiming Xie, Zhiguo Wang, Guoxu Zhang

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引用次数: 0

Abstract

Introduction: The retinal microvasculature has been definitively linked to a variety of diseases, such as ophthalmological, cardiovascular, and other medical conditions. Precisely identifying the retinal microvasculature is crucial for early detection and monitoring of these diseases. While the majority of existing neural network-based research has primarily focused on utilizing the green channel of fundus images for vessel segmentation, it is important to acknowledge the potential value of other channels in this process.

Methods: This study introduces RetinalVasNet, a new method aimed at enhancing the accuracy and effectiveness of retinal vascular segmentation by implementing a sophisticated neural network architecture and incorporating multi-channel fundus images.

Results: Our experimental results demonstrate that RetinalVasNet outperforms previous research in most performance metrics.

Discussion: The findings suggest that each channel provides unique contributions to the vascular segmentation process, emphasizing the importance of incorporating multiple channels for accurate and comprehensive segmentation.

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视网膜血管网：一种鲁棒视网膜微血管检测的深度学习方法。

视网膜微血管已明确地与多种疾病，如眼科、心血管和其他医疗条件有关。准确识别视网膜微血管对这些疾病的早期发现和监测至关重要。虽然现有的大多数基于神经网络的研究主要集中在利用眼底图像的绿色通道进行血管分割，但重要的是要认识到在这一过程中其他通道的潜在价值。方法：引入一种新的视网膜血管分割方法RetinalVasNet，该方法采用复杂的神经网络架构，结合多通道眼底图像，提高视网膜血管分割的准确性和有效性。结果：我们的实验结果表明，RetinalVasNet在大多数性能指标上优于先前的研究。讨论：研究结果表明，每个通道对血管分割过程都有独特的贡献，强调了合并多个通道对准确和全面分割的重要性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Frontiers in Molecular Biosciences Biochemistry, Genetics and Molecular Biology-Biochemistry

CiteScore

7.20

自引率

4.00%

发文量

1361

审稿时长

14 weeks

期刊介绍： Much of contemporary investigation in the life sciences is devoted to the molecular-scale understanding of the relationships between genes and the environment — in particular, dynamic alterations in the levels, modifications, and interactions of cellular effectors, including proteins. Frontiers in Molecular Biosciences offers an international publication platform for basic as well as applied research; we encourage contributions spanning both established and emerging areas of biology. To this end, the journal draws from empirical disciplines such as structural biology, enzymology, biochemistry, and biophysics, capitalizing as well on the technological advancements that have enabled metabolomics and proteomics measurements in massively parallel throughput, and the development of robust and innovative computational biology strategies. We also recognize influences from medicine and technology, welcoming studies in molecular genetics, molecular diagnostics and therapeutics, and nanotechnology. Our ultimate objective is the comprehensive illustration of the molecular mechanisms regulating proteins, nucleic acids, carbohydrates, lipids, and small metabolites in organisms across all branches of life. In addition to interesting new findings, techniques, and applications, Frontiers in Molecular Biosciences will consider new testable hypotheses to inspire different perspectives and stimulate scientific dialogue. The integration of in silico, in vitro, and in vivo approaches will benefit endeavors across all domains of the life sciences.