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扩散磁共振成像纤维束示踪可视化工具的分类指南。

A taxonomic guide to diffusion MRI tractography visualization tools.

作者信息

Laamoumi Miriam, Hendriks Tom, Chamberland Maxime

机构信息

Department of Mathematics and Computer Science, Eindhoven University of Technology, Eindhoven, The Netherlands.

Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.

出版信息

NMR Biomed. 2025 Jan;38(1):e5267. doi: 10.1002/nbm.5267. Epub 2024 Oct 7.

Abstract

Visualizing neuroimaging data is a key step in evaluating data quality, interpreting results, and communicating findings. This survey focuses on diffusion MRI tractography, which has been widely used in both research and clinical domains within the neuroimaging community. With an increasing number of tractography tools and software, navigating this landscape poses a challenge, especially for newcomers. A systematic exploration of a diverse range of features is proposed across 27 research tools, delving into their main purpose and examining the presence or absence of prevalent visualization and interactive techniques. The findings are structured within a proposed taxonomy, providing a comprehensive overview. Insights derived from this analysis will help (novice) researchers, clinicians, and developers in identifying knowledge gaps and navigating the landscape of tractography visualization tools.

摘要

可视化神经影像数据是评估数据质量、解释结果和交流研究发现的关键步骤。本调查聚焦于扩散磁共振成像纤维束示踪技术,该技术在神经影像学界的研究和临床领域都得到了广泛应用。随着纤维束示踪工具和软件的数量不断增加,在这一领域中找到方向颇具挑战,尤其是对于新手而言。本文针对27种研究工具,对一系列不同的功能进行了系统探索,深入研究其主要用途,并考察常见可视化和交互技术的有无情况。研究结果按照提出的分类法进行组织,提供了全面的概述。从该分析中获得的见解将有助于(新手)研究人员、临床医生和开发人员识别知识空白,并在纤维束示踪可视化工具领域找到方向。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6ddd/11631367/abd52d2d18da/NBM-38-e5267-g012.jpg

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