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 thousands of subjects to understand subtle abnormalities in  brain's white matter connectivity across disease populations. Besides connectivity differences, researchers are also interested in investigating distributions of biologically sensitive dMRI derived metrics across subject groups . Existing software products focus solely on the anatomy or are not intuitive and 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 and scalable visualization of brain fiber clusters in 2D and 3D  . With FiberStars, researchers can analyze and compare multiple subjects in large collections of brain fibers  . To evaluate the usability of our software, we performed a quantitative user study. We asked  non-experts to find patterns in a large tractography dataset with either FiberStars or AFQ-Browser, an existing dMRI exploration tool. Our results show that participants using FiberStars can navigate extensive collections of tractography faster and more accurately . We discuss our findings and provide an analysis of the requirements for comparative visualizations of tractography data . All our research, software, and results are available openly.
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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