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README
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Volume Rendering documentation
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Volume Rendering Documentation and Information
Volume Rendering source code can be found in
toolbox/src/exampleCode/volumeRendering
and in toolbox/src/tutorials/OGLT/Examples/VolumeRendering.
* Building an OpenGL Volume Renderer, 1996
The ability to produce volume-rendered images interactively opens the
door to a host of new application capabilities. Volumetric data is
commonplace today. Radiologists use magnetic resonance images (MRI) and
computed tomography (CT) data in clinical diagnoses. Geophysicists map
and study three-dimensional voxel Earth models. Environmentalists
examine pollution clouds in the air and plumes underground. Chemists
and biologists visualize potential fields around molecules and
meteorologists study weather patterns. With so many disciplines
actively engaging in the study and examination of three-dimensional
data, today's software developers need to understand techniques used to
visualize this data. You can use three-dimensional texture mapping, an
extension of two-dimensional texture mapping, as the basis for building
fast, flexible volume renderers.
This article tells you how to build an interactive, texture
mapping-based volume renderer in OpenGL. The article also includes a
pseudo-coded volume renderer to help illustrate particular concepts.
This work lives in the
toolbox/src/exampleCode/volumeRendering/volren-6/doc/www directory.
* Interactive Volume Rendering Using Advanced Graphics Architectures:
o html format
o compressed PostScript
o uncompressed PostScript
This paper articulates a good alternative use of texture mapping. Its
description explores some of what's involved in doing volume rendering.
* Accelerated Volume Rendering and Tomographic Reconstruction Using
Texture Mapping Hardware
o compressed PostScript format
o uncompressed PostScript
ABSTRACT: Volume rendering and reconstruction centers around solving
two related integral equations: a volume rendering integral (a
generalized Radon transform) and a filtered backprojection integral
(the inverse Radon transform). Both of these equations are of the same
mathematical form and can be dimensionally decomposed and approximated
using Riemann sums over a series of resampled images. When viewed as a
form of texture mapping and frame buffer accumulation, enormous
hardware enabled performance acceleration is possible.
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Copyright ⌐ 1995-96, Silicon Graphics, Inc.