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1991 - 2023年视神经成像的研究进展:一项文献计量分析

Research progress of optic nerve imaging during 1991-2023: a bibliometric analysis.

作者信息

Zhang Haiyang, Lee Xin Ning, Tan Kexin, Zhang Qianyue, Li Jipeng, Zhou Huifang, Song Xuefei, Fan Xianqun

机构信息

Department of Ophthalmology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai, China.

出版信息

Quant Imaging Med Surg. 2024 Sep 1;14(9):6566-6578. doi: 10.21037/qims-24-870. Epub 2024 Aug 28.

Abstract

BACKGROUND

Optic nerve imaging is crucial for diagnosing and understanding optic neuropathies because it provides detailed visualization of the nerve's structure and pathologies through advanced modalities. This study conducted a bibliometric analysis within the field of optic nerve imaging, aiming to pinpoint the latest research trends and focal points in optic nerve imaging.

METHODS

The core literature on optic nerve imaging published between January 1991 and August 2023 was retrieved from the Web of Science Core Collection. The analysis and visualization of scientific productivity and emerging trends were facilitated through the utilization of Bibliometrix software, CiteSpace, Gephi, VOSviewer, R software, and Python.

RESULTS

In total, 15,247 publications on optic nerve imaging were included in the analysis. Notably, the top 3 journals contributing to this field were , , and the . This research on optic nerve imaging extended across 97 countries, with the USA leading in research endeavors. Noteworthy burst term analysis revealed that "Segmentation" and "Machine learning" are gaining attention. Additionally, the Latent Dirichlet Allocation model indicated that image processing has been a hotspot in recent years.

CONCLUSIONS

This study revealed the research trends, hotspots, and emerging topics in optic nerve imaging through bibliometric analysis and network visualization. At present, the research focus is directed towards employing artificial intelligence for image post-processing. The findings of this study offer valuable insights into future research direction and clinical applications.

摘要

背景

视神经成像对于诊断和理解视神经病变至关重要,因为它通过先进的方式提供了神经结构和病变的详细可视化。本研究对视神经成像领域进行了文献计量分析,旨在确定视神经成像的最新研究趋势和重点。

方法

从科学网核心合集检索了1991年1月至2023年8月期间发表的关于视神经成像的核心文献。通过使用Bibliometrix软件、CiteSpace、Gephi、VOSviewer、R软件和Python促进了对科学生产力和新兴趋势的分析和可视化。

结果

分析共纳入了15247篇关于视神经成像的出版物。值得注意的是,该领域贡献最大的前3本期刊分别是《 》、《 》和《 》。这项关于视神经成像的研究涉及97个国家,美国在研究工作方面处于领先地位。值得注意的突发词分析表明,“分割”和“机器学习”正受到关注。此外,潜在狄利克雷分配模型表明图像处理近年来一直是一个热点。

结论

本研究通过文献计量分析和网络可视化揭示了视神经成像的研究趋势、热点和新兴主题。目前,研究重点是将人工智能应用于图像后处理。本研究结果为未来的研究方向和临床应用提供了有价值的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3464/11400669/81e3a7546a74/qims-14-09-6566-f1.jpg

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