论文标题

Fiberstars:多个受试者之间扩散拖拉学数据的视觉比较

FiberStars: Visual Comparison of Diffusion Tractography Data between Multiple Subjects

论文作者

Franke, Loraine, Weidele, Daniel Karl I., Zhang, Fan, Cetin-Karayumak, Suheyla, Pieper, Steve, O'Donnell, Lauren J., Rathi, Yogesh, Haehn, Daniel

论文摘要

来自高维扩散磁共振成像(DMRI)数据的拖拉术允许大脑的结构连通性分析。最近的DMRI研究旨在比较受试者群体和疾病人群之间的连通性模式,以了解大脑白质连通性的微妙异常以及生物敏感的DMRI衍生指标的分布。现有的软件产品仅关注解剖学,不直观或限制多个受试者的比较。在本文中,我们介绍了Fiberstars的设计和实现,Fiberstars是一种用于拖拉图数据的视觉分析工具,允许将现有3D解剖结合与紧凑的2D可视化的脑纤维簇进行交互式可视化。借助纤维恒星,研究人员可以使用不同的观点分析和比较大量脑纤维中的多个受试者。为了评估软件的可用性,我们进行了定量用户研究。我们要求域专家和非专家在带有纤维恒星或现有DMRI探索工具的拖拉数据集中找到模式。我们的结果表明,使用纤维标准的参与者可以更快,更准确地浏览大量拖拉机集。我们所有的研究,软件和结果均可公开获得。

Tractography from high-dimensional diffusion magnetic resonance imaging (dMRI) data allows brain's structural connectivity analysis. Recent dMRI studies aim to compare connectivity patterns across subject groups and disease populations to understand subtle abnormalities in the brain's white matter connectivity and distributions of biologically sensitive dMRI derived metrics. Existing software products focus solely on the anatomy, are not intuitive or restrict the comparison of multiple subjects. In this paper, we present the design and implementation of FiberStars, a visual analysis tool for tractography data that allows the interactive visualization of brain fiber clusters combining existing 3D anatomy with compact 2D visualizations. With FiberStars, researchers can analyze and compare multiple subjects in large collections of brain fibers using different views. To evaluate the usability of our software, we performed a quantitative user study. We asked domain experts and non-experts to find patterns in a tractography dataset with either FiberStars or an existing dMRI exploration tool. Our results show that participants using FiberStars can navigate extensive collections of tractography faster and more accurately. All our research, software, and results are available openly.

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