FiberStars: Visual Comparison of Diffusion Tractography Data between Multiple Subjects

May 16, 2020 Β· Declared Dead Β· πŸ› IEEE Pacific Visualization Symposium

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Authors Loraine Franke, Daniel Karl I. Weidele, Fan Zhang, Suheyla Cetin-Karayumak, Steve Pieper, Lauren J. O'Donnell, Yogesh Rathi, Daniel Haehn arXiv ID 2005.08090 Category cs.HC: Human-Computer Interaction Cross-listed cs.AI Citations 6 Venue IEEE Pacific Visualization Symposium Last Checked 4 months ago
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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