Paper
25 March 1999 Volumetric measurements from an isosurface algorithm
Jennifer J. Hare, John Grosh, Charles E. Schmitt
Author Affiliations +
Proceedings Volume 3643, Visual Data Exploration and Analysis VI; (1999) https://doi.org/10.1117/12.342836
Event: Electronic Imaging '99, 1999, San Jose, CA, United States
Abstract
Scientific visualization methods have become the new standards for analyzing scientific datasets. However, while these visualization routines provide an excellent qualitative means for data analysis, many researchers still require quantitative information about their data. This paper describes how the marching cubes iso-surface algorithm can be modified to produce not only the qualitative information about the shape of a surface but also some quantitative information regarding the volume of space contained within or beneath that surface. The original marching cubes algorithm decomposes a dataset into cubes based on the grid structure provided. It then searches each cube, determining whether or not the surface intersects that particular cube. During this search, volume calculations can be performed for each cube or partial cube that is contained within or beneath the surface. The results of these calculations can then be summed to obtain a measurement for the volume of space that is within or beneath the surface. These additional tasks can easily be incorporated into the marching cubes algorithm, providing the researcher with a volumetric measurement to support the more qualitative visual information generally produced by an iso-surface algorithm.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jennifer J. Hare, John Grosh, and Charles E. Schmitt "Volumetric measurements from an isosurface algorithm", Proc. SPIE 3643, Visual Data Exploration and Analysis VI, (25 March 1999); https://doi.org/10.1117/12.342836
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Cited by 3 scholarly publications.
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KEYWORDS
Visualization

Algorithm development

Analytical research

Information visualization

Optical spheres

Visual analytics

Data analysis

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