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Proceedings Paper

Brain Slicer: a high-performance Internet-based neuromedical imaging system
Author(s): Rongkai Zhao; Tao Tao; Michael Gabriel; Geneva Belford
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Paper Abstract

In this paper, we present a neuro-medical imaging system called the Brain Slicer, which allows neuroscientists to construct a three-dimensional digital brain atlas from an array of high-resolution parallel section images and obtain arbitrary oblique section images from the digital atlas. This application is based on a new data structure, the Scalable Hyper-Space File (SHSF). The SHSF is a generalized data structure that can represent a hyperspace of any dimension. The two-dimensional SHSF is a scalable linear quadtree and the three-dimensional SHSF is a scalable linear octree. Unlike the normal linear quadtree and octree, the data structure uses a scalable linear coding scheme. It recursively uses fixed-length linear code to encode the hyperspace, which is efficient in terms of storage space and accessing speed. The structure lends itself well to pipelined parallel operations in constructing the volumetric data set, so that it enjoys excellent performance even though the huge data set imposes heavy disk I/O requirements. The data structure can provide different levels of detail; therefore it can be used in an environment where the bandwidth and computation power is limited, such as the Internet and slow desktop computers. We envision that this methodology can be used in many areas other than neuro-medical imaging.

Paper Details

Date Published: 12 March 2002
PDF: 12 pages
Proc. SPIE 4665, Visualization and Data Analysis 2002, (12 March 2002); doi: 10.1117/12.458801
Show Author Affiliations
Rongkai Zhao, Univ. of Illinois/Urbana-Champaign (United States)
Tao Tao, Univ. of Illinois/Urbana-Champaign (United States)
Michael Gabriel, Univ. of Illinois/Urbana-Champaign (United States)
Geneva Belford, Univ. of Illinois/Urbana-Champaign (United States)

Published in SPIE Proceedings Vol. 4665:
Visualization and Data Analysis 2002
Robert F. Erbacher; Philip C. Chen; Matti Groehn; Jonathan C. Roberts; Craig M. Wittenbrink, Editor(s)

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