FiberStars: Visual Comparison of Diffusion Tractography Data between Multiple Subjects

Loraine Franke, D. Weidele, Fan Zhang, Suheyla Cetin Karayumak, Steve Pieper, L. O’Donnell, Y. Rathi, D. Haehn
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引用次数: 3

Abstract

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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FiberStars:多受试者间弥散造影数据的视觉比较
从高维扩散磁共振成像(dMRI)数据中获得的神经束图可以分析大脑的结构连通性。最近的dMRI研究旨在比较不同受试者组和疾病人群的连接模式,以了解大脑白质连接的细微异常和dMRI衍生的生物敏感指标的分布。现有的软件产品只关注解剖,不直观或限制多科目的比较。在本文中,我们介绍了FiberStars的设计和实现,这是一种用于神经束造影数据的可视化分析工具,可以将现有的3D解剖与紧凑的2D可视化相结合,实现脑纤维簇的交互式可视化。有了FiberStars,研究人员可以用不同的视角分析和比较大量大脑纤维中的多个受试者。为了评估我们软件的可用性,我们进行了一个定量的用户研究。我们要求领域专家和非专家使用FiberStars或现有的dMRI勘探工具在轨迹图数据集中找到模式。我们的研究结果表明,使用FiberStars的参与者可以更快、更准确地导航广泛的束状图集合。我们所有的研究、软件和结果都是公开的。
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