Abstract
Dimension Reduction is the process of transfering high-dimensional data into lower dimensions while maintaining the original intrinsic structures. This technique of finding low-dimensional embedding from high-dimensional data is important for visualizing dense 3D DTI fibers because it is hard to visualize and analyze the fiber tracts with high geometric, spatial, and anatomical complexity. Color-mapping, selection, and abstraction are widely used in DTI fiber visualization to depict the properties of fiber models. Nonetheless, visual clutters and occlusion in 3D space make it hard to grasp even a few thousand fibers. In addition, real time interaction (exploring and navigating) on such complex 3D models consumes large amount of CPU/GPU power. Converting DTI fiber to 2D or 3D points with dimension reduction techniques provides a complimentary visualization for these fibers. This chapter analyzes and compares dimension reduction methods for DTI fiber models. An interaction interface augments the 3D visualization with a 2D representation that contains a low-dimensional embedding of the DTI fibers. To achieve real-time interaction, the framework is implemented with GPU programming.
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Acknowledgements
This work is partially supported by 973 program of China (2009CB320800), NSF of China (No.60873123) and Mississippi State University. We thank Dr. David Tate for providing the brain data sets.
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Yang, X., Wu, R., Ding, Z., Chen, W., Zhang, S. (2012). A Comparative Analysis of Dimension Reduction Techniques for Representing DTI Fibers as 2D/3D Points. In: Laidlaw, D., Vilanova, A. (eds) New Developments in the Visualization and Processing of Tensor Fields. Mathematics and Visualization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27343-8_9
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DOI: https://doi.org/10.1007/978-3-642-27343-8_9
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