NDLI: Parallel reflective symmetry transformation for volume data

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Content Provider	ACM Digital Library
Author	Hong, Y. Shen, H. W.
Abstract	Many volume data possess symmetric features that can be clearly observed, for example, those existed in diffusion tensor image data sets. The exploitations of symmetries for volume data sets, however, are relatively limited due to the prohibitive computational cost of detecting the symmetries. In this paper we present an efficient parallel algorithm for symmetry computation in volume data represented by regular grids. Optimization is achieved by converting the raw data into a hierarchical tree-like structure. We design a novel algorithm to partition the tree and distribute the data among processors to minimize the data dependency at run time. The computed symmetries are useful for several volume data applications, including POF minimal opacity selection, transfer function generation and slice position selection.
Starting Page	77
Ending Page	83
Page Count	7
ISBN	9783905673500
ISSN	1727348X
DOI	10.2312/EGPGV/EGPGV07/077-083
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2007-05-20
Publisher Place	Goslar
Access Restriction	Subscribed
Content Type	Text
Resource Type	Article

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Parallel reflective symmetry transformation for volume data