TRAKO: Efficient Transmission of Tractography Data for Visualization
April 26, 2020 Β· Declared Dead Β· π International Conference on Medical Image Computing and Computer-Assisted Intervention
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Authors
Daniel Haehn, Loraine Franke, Fan Zhang, Suheyla Cetin Karayumak, Steve Pieper, Lauren O'Donnell, Yogesh Rathi
arXiv ID
2004.13630
Category
eess.IV: Image & Video Processing
Cross-listed
cs.CV,
cs.GR,
q-bio.QM
Citations
8
Venue
International Conference on Medical Image Computing and Computer-Assisted Intervention
Last Checked
4 months ago
Abstract
Fiber tracking produces large tractography datasets that are tens of gigabytes in size consisting of millions of streamlines. Such vast amounts of data require formats that allow for efficient storage, transfer, and visualization. We present TRAKO, a new data format based on the Graphics Layer Transmission Format (glTF) that enables immediate graphical and hardware-accelerated processing. We integrate a state-of-the-art compression technique for vertices, streamlines, and attached scalar and property data. We then compare TRAKO to existing tractography storage methods and provide a detailed evaluation on eight datasets. TRAKO can achieve data reductions of over 28x without loss of statistical significance when used to replicate analysis from previously published studies.
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