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	<title>GPGPU &#187; Tag: Volume Rendering :: GPGPU.org</title>
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	<link>http://gpgpu.org</link>
	<description>General-Purpose Computation on Graphics Hardware</description>
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		<title>Physically based lighting for volumetric data with Exposure Render</title>
		<link>http://gpgpu.org/2011/10/27/exposure-render</link>
		<comments>http://gpgpu.org/2011/10/27/exposure-render#comments</comments>
		<pubDate>Thu, 27 Oct 2011 08:52:35 +0000</pubDate>
		<dc:creator>dom</dc:creator>
				<category><![CDATA[Developer Resources]]></category>
		<category><![CDATA[Research]]></category>
		<category><![CDATA[Monte Carlo Simulation]]></category>
		<category><![CDATA[NVIDIA CUDA]]></category>
		<category><![CDATA[Open Source]]></category>
		<category><![CDATA[Ray Tracing]]></category>
		<category><![CDATA[Volume Rendering]]></category>

		<guid isPermaLink="false">http://gpgpu.org/?p=4083</guid>
		<description><![CDATA[Exposure Render is a Direct Volume Rendering Application that applies progressive Monte Carlo raytracing, coupled with physically based light transport to heterogeneous volumetric data. Exposure Render enables the configuration of any number of arbitrarily shaped area lights, models a real-world camera, including its lens and aperture, and incorporates complex materials, whilst still maintaining interactive display [...]]]></description>
			<content:encoded><![CDATA[<p><a href="http://code.google.com/p/exposure-render/" target="_blank"><iframe src="http://www.youtube.com/embed/cZaPIEo6PPs" frameborder="0" align="right" width="200" height="165"></iframe>Exposure Render</a> is a Direct Volume Rendering Application that applies progressive Monte Carlo raytracing, coupled with physically based light transport to heterogeneous volumetric data. Exposure Render enables the configuration of any number of arbitrarily shaped area lights, models a real-world camera, including its lens and aperture, and incorporates complex materials, whilst still maintaining interactive display updates. It features both surface and volumetric scattering, and applies noise reduction to remove the unwanted startup noise associated with progressive Monte Carlo rendering. The complete implementation is available in source and binary forms under a permissive free software license.</p>
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		<title>Efficient High-Quality Volume Rendering of SPH Data</title>
		<link>http://gpgpu.org/2010/09/27/volume-rendering-sph-data</link>
		<comments>http://gpgpu.org/2010/09/27/volume-rendering-sph-data#comments</comments>
		<pubDate>Mon, 27 Sep 2010 07:14:26 +0000</pubDate>
		<dc:creator>dom</dc:creator>
				<category><![CDATA[Research]]></category>
		<category><![CDATA[NVIDIA CUDA]]></category>
		<category><![CDATA[Papers]]></category>
		<category><![CDATA[SPH]]></category>
		<category><![CDATA[Visualization]]></category>
		<category><![CDATA[Volume Rendering]]></category>

		<guid isPermaLink="false">http://gpgpu.org/?p=2781</guid>
		<description><![CDATA[Abstract: High quality volume rendering of SPH data requires a complex order-dependent resampling of particle quantities along the view rays. In this paper we present an efficient approach to perform this task using a novel view-space discretization of the simulation domain. Our method draws upon recent work on GPU-based particle voxelization for the efficient resampling [...]]]></description>
			<content:encoded><![CDATA[<p><a href="http://gpgpu.org/wp/wp-content/uploads/2010/09/SPHSplattingTeaser.jpg"><img class="alignright size-thumbnail wp-image-2788" title="SPHSplattingTeaser" src="http://gpgpu.org/wp/wp-content/uploads/2010/09/SPHSplattingTeaser-150x150.jpg" alt="Efficient High-Quality Volume Rendering of SPH Data" width="150" height="150" /></a>Abstract:</p>
<blockquote><p>High quality volume rendering of SPH data requires a complex order-dependent resampling of particle quantities along the view rays. In this paper we present an efficient approach to perform this task using a novel view-space discretization of the simulation domain. Our method draws upon recent work on GPU-based particle voxelization for the efficient resampling of particles into uniform grids. We propose a new technique that leverages a perspective grid to adaptively discretize the view-volume, giving rise to a continuous level-of-detail sampling structure and reducing memory requirements compared to a uniform grid. In combination with a level-of-detail representation of the particle set, the perspective grid allows effectively reducing the amount of primitives to be processed at run-time. We demonstrate the quality and performance of our method for the rendering of fluid and gas dynamics SPH simulations consisting of many millions of particles.</p></blockquote>
<p>(Roland Fraedrich, Stefan Auer, and Rüdiger Westermann:<em> “Efficient High-Quality Volume Rendering of SPH Data”</em>, IEEE Transactions on Visualization and Computer Graphics (Proceedings of IEEE Visualization 2010), vol. 16, no. 6, Nov.-Dec. 2010, <a href="http://wwwcg.in.tum.de/Research/Publications/SPHSplatting" target="_blank">Link to project webpage including paper, pictures and video</a>)</p>
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		<slash:comments>3</slash:comments>
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		<title>HPMC open-source GPU volumetric iso-surface extraction library</title>
		<link>http://gpgpu.org/2009/11/30/hpmc-iso-surface-library</link>
		<comments>http://gpgpu.org/2009/11/30/hpmc-iso-surface-library#comments</comments>
		<pubDate>Tue, 01 Dec 2009 01:09:47 +0000</pubDate>
		<dc:creator>Mark Harris</dc:creator>
				<category><![CDATA[Developer Resources]]></category>
		<category><![CDATA[Research]]></category>
		<category><![CDATA[Open Source]]></category>
		<category><![CDATA[OpenGL]]></category>
		<category><![CDATA[Volume Rendering]]></category>
		<category><![CDATA[Volumetric Reconstruction]]></category>

		<guid isPermaLink="false">http://gpgpu.org/?p=1980</guid>
		<description><![CDATA[HPMC is a small OpenGL/C/C++-library that extracts iso-surfaces of volumetric data directly on the GPU. The library analyzes a lattice of scalar values describing a scalar field that is either stored in a Texture3D or can be accessed through an application-provided snippet of shader code. The output is a sequence of vertex positions and normals [...]]]></description>
			<content:encoded><![CDATA[<p><a href="http://www.sintef.no/hpmc">HPMC</a> is a small OpenGL/C/C++-library that extracts iso-surfaces of volumetric data directly on the GPU.</p>
<p>The library analyzes a lattice of scalar values describing a scalar field that is either stored in a Texture3D or can be accessed through an application-provided snippet of shader code. The output is a sequence of vertex positions and normals that form a triangulation of the iso-surface. HPMC provides traversal code to be included in an application vertex shader, which allows direct extraction in the vertex shader. Using the OpenGL transform feedback mechanism, the triangulation can be stored directly into a buffer object.</p>
<p>(C. Dyken, G. Ziegler, C. Theobalt, H.-P. Seidel, <a href="http://www.ingentaconnect.com/content/bpl/cgf/2008/00000027/00000008/art00003">High-speed Marching Cubes using Histogram Pyramids</a>, Computer Graphics Forum 27 (8), 2008.)</p>
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		<title>Fourier Volume Rendering on the GPU  Using a Split-Stream FFT</title>
		<link>http://gpgpu.org/2005/03/01/fourier-volume-rendering-on-the-gpu-using-a-split-stream-fft</link>
		<comments>http://gpgpu.org/2005/03/01/fourier-volume-rendering-on-the-gpu-using-a-split-stream-fft#comments</comments>
		<pubDate>Tue, 01 Mar 2005 04:50:00 +0000</pubDate>
		<dc:creator>Mark Harris</dc:creator>
				<category><![CDATA[Research]]></category>
		<category><![CDATA[FFT]]></category>
		<category><![CDATA[Papers]]></category>
		<category><![CDATA[Signal Processing]]></category>
		<category><![CDATA[Volume Rendering]]></category>

		<guid isPermaLink="false">http://www.gpgpu.org/cgi-bin/blosxom.cgi/ImageAndVolumeProcessing/jansenSplitStreamFFT.html</guid>
		<description><![CDATA[This paper by Jansen et al. describes how to utilize current commodity graphics hardware to perform Fourier volume rendering directly on the GPU. The paper presents a novel implementation of the Fast Fourier Transform: This Split-Stream-FFT maps the recursive structure of the FFT to the GPU in an efficient way. Additionally, high-quality resampling within the [...]]]></description>
			<content:encoded><![CDATA[<p>This paper by Jansen et al. describes how to utilize current commodity graphics hardware to perform Fourier volume rendering directly on the GPU. The paper presents a novel implementation of the Fast Fourier Transform: This Split-Stream-FFT maps the recursive structure of the FFT to the GPU in an efficient way. Additionally, high-quality resampling within the frequency domain is discussed. The implementation enables visualization of large volumetric data sets at interactive frame rates on a mid-range computer system. (<a href="http://www.caesar.de/uploads/media/C04-3.pdf" target="_blank" title="Fourier Volume Rendering on the GPU  Using a Split-Stream FFT">Fourier Volume Rendering on the GPU Using a Split-Stream FFT</a>)</p>
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		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Accelerating 3D Convolution using Graphics Hardware</title>
		<link>http://gpgpu.org/2004/02/19/accelerating-3d-convolution-using-graphics-hardware</link>
		<comments>http://gpgpu.org/2004/02/19/accelerating-3d-convolution-using-graphics-hardware#comments</comments>
		<pubDate>Thu, 19 Feb 2004 13:32:00 +0000</pubDate>
		<dc:creator>Mark Harris</dc:creator>
				<category><![CDATA[Research]]></category>
		<category><![CDATA[Papers]]></category>
		<category><![CDATA[Signal Processing]]></category>
		<category><![CDATA[Volume Rendering]]></category>

		<guid isPermaLink="false">http://www.gpgpu.org/cgi-bin/blosxom.cgi/ImageAndVolumeProcessing/hopf3DConvolution.html</guid>
		<description><![CDATA[This paper from the VIS Group Stuttgart shows the first volume filtering algorithm that uses OpenGL for the convolution process. Filtering volume data is useful for noise reduction, feature detection, and segmentation. The process is significantly accelerated on SGI graphics workstations with hardware support for two-dimensional image convolution in the frame buffer. Generic 3D convolution [...]]]></description>
			<content:encoded><![CDATA[<p>This paper from the <a href="http://www.vis.uni-stuttgart.de/" title="VIS Group Stuttgart" target="_blank">VIS Group Stuttgart</a> shows the first volume filtering algorithm that uses OpenGL for the convolution process. Filtering volume data is useful for noise reduction, feature detection, and segmentation. The process is significantly accelerated on SGI graphics workstations with hardware support for two-dimensional image convolution in the frame buffer. Generic 3D convolution can be added as a powerful tool in interactive volume visualization toolkits. See also the <a href="http://www.vis.uni-stuttgart.de/eng/research/fields/current/hwfilters/" title="project page" target="_blank">project page</a> for more about hardware-based filtering. (<a href="http://www.vis.uni-stuttgart.de/eng/research/pub/pub1999/vis99hopf.pdf" title="Accelerating 3D Convolution using Graphics Hardware" target="_blank">Accelerating 3D Convolution using Graphics Hardware</a>. <a href="http://www.mshopf.de/" title="Matthias Hopf" target="_blank">Matthias Hopf</a> and <a href="http://www.vis.uni-stuttgart.de/~ertl/" title="Thomas Ertl" target="_blank">Thomas Ertl</a>. Proc. Visualization 1999, pp 471&#8211;474.)</p>
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		<slash:comments>0</slash:comments>
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		<title>A Streaming Narrow Band Algorithm: Interactive Computation and Visualization of Level Sets</title>
		<link>http://gpgpu.org/2003/12/15/a-streaming-narrow-band-algorithm-interactive-computation-and-visualization-of-level-sets</link>
		<comments>http://gpgpu.org/2003/12/15/a-streaming-narrow-band-algorithm-interactive-computation-and-visualization-of-level-sets#comments</comments>
		<pubDate>Mon, 15 Dec 2003 20:09:00 +0000</pubDate>
		<dc:creator>Mark Harris</dc:creator>
				<category><![CDATA[Research]]></category>
		<category><![CDATA[Papers]]></category>
		<category><![CDATA[Signal Processing]]></category>
		<category><![CDATA[Volume Rendering]]></category>

		<guid isPermaLink="false">http://www.gpgpu.org/cgi-bin/blosxom.cgi/ImageAndVolumeProcessing/lefohnStreamingNarrowBandLevelSet.html</guid>
		<description><![CDATA[This TVCG paper is an extended version of a Vis 2003 paper, with significantly more detail about the time-dependent, sparse-grid GPU computation strategy used in the level-set solver. The paper describes a 3D-to-2D virtual memory address scheme for packing the narrow-band data into GPU memory. It also adds detail about the GPU-based distance transform computation [...]]]></description>
			<content:encoded><![CDATA[<p>This TVCG paper is an extended version of a <a href="http://vis.computer.org/vis2003/" title="Visualization 2003" target="_blank">Vis 2003</a> paper, with significantly more detail about the time-dependent, sparse-grid GPU computation strategy used in the level-set solver. The paper describes a 3D-to-2D virtual memory address scheme for packing the narrow-band data into GPU memory. It also adds detail about the GPU-based distance transform computation and the GPU-to-CPU message passing approach. Lastly, the paper describes a volume rendering algorithm for rendering compressed data that provides on-the-fly reconstruction, full trilinear interpolation, and the ability to render from any viewpoint without data duplication. (<a href="http://graphics.cs.ucdavis.edu/~lefohn/rls/visLevelSet/">A Streaming Narrow Band Algorithm: Interactive Computation and Visualization of Level Sets</a>. <a href="http://graphics.cs.ucdavis.edu/~lefohn/">A. Lefohn</a>, <a href="http://www.cs.utah.edu/~jmk/" title="Joe Kniss" target="_blank">J. Kniss</a>, <a href="http://www.sci.utah.edu/personnel/hansen.html" title="Chuck Hansen" target="_blank">C. Hansen</a>, and <a href="http://www.sci.utah.edu/personnel/whitaker.html" title="Ross Whitaker" target="_blank">R. Whitaker</a>. <a href="http://www.computer.org/tvcg/" title="TVCG Website" target="_blank">Transactions on Visualization and Computer Graphics</a>.)</p>
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		<slash:comments>0</slash:comments>
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		<item>
		<title>Dynamic Volume Computation and Visualization on the GPU</title>
		<link>http://gpgpu.org/2003/12/15/dynamic-volume-computation-and-visualization-on-the-gpu</link>
		<comments>http://gpgpu.org/2003/12/15/dynamic-volume-computation-and-visualization-on-the-gpu#comments</comments>
		<pubDate>Mon, 15 Dec 2003 19:44:00 +0000</pubDate>
		<dc:creator>Mark Harris</dc:creator>
				<category><![CDATA[Events]]></category>
		<category><![CDATA[Research]]></category>
		<category><![CDATA[Tutorials & Courses]]></category>
		<category><![CDATA[Volume Rendering]]></category>

		<guid isPermaLink="false">http://www.gpgpu.org/cgi-bin/blosxom.cgi/ImageAndVolumeProcessing/lefohnDynVolumVis2003.html</guid>
		<description><![CDATA[This IEEE Visualization 2003 tutorial presentation by Aaron Lefohn gives a high-level overview of dynamic volume computation and visualization on GPUs. The talk is part of the tutorial]]></description>
			<content:encoded><![CDATA[<p>This <a href="http://vis.computer.org/vis2003/">IEEE Visualization 2003</a> tutorial presentation by <a href="http://graphics.cs.ucdavis.edu/~lefohn/" title="Aaron Lefohn" target="_blank">Aaron Lefohn</a> gives a high-level overview of dynamic volume computation and visualization on GPUs. The talk is part of the tutorial <a href="href="http://www.vis.uni-stuttgart.de/vis03_tutorial/" title="Volume Visualization Tutorial" target="_blank">Interactive Visualization of Volumetric Data on Consumer PC Hardware</a>. The first half of the presentation discusses various memory layout options for dynamic volume computation, and the implications of each option on computation and rendering. The second half discusses optimizations and load balancing between the various computational resources: CPU, vertex processor, rasterizer, and fragment processor. (<a href="http://www.vis.uni-stuttgart.de/vis03_tutorial/lefohn.pdf" title="Dynamic Volume Computation and Visualization on the GPU" target="_blank">Dynamic Volume<br />
Computation and Visualization on the GPU</a>, by <a href="http://graphics.cs.ucdavis.edu/~lefohn/" title="Aaron Lefohn" target="_blank">Aaron Lefohn</a>)</p>
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		<item>
		<title>Acceleration Techniques for GPU-based Volume Rendering</title>
		<link>http://gpgpu.org/2003/09/03/acceleration-techniques-for-gpu-based-volume-rendering</link>
		<comments>http://gpgpu.org/2003/09/03/acceleration-techniques-for-gpu-based-volume-rendering#comments</comments>
		<pubDate>Wed, 03 Sep 2003 19:27:00 +0000</pubDate>
		<dc:creator>Mark Harris</dc:creator>
				<category><![CDATA[Research]]></category>
		<category><![CDATA[Computer Graphics]]></category>
		<category><![CDATA[Papers]]></category>
		<category><![CDATA[Volume Rendering]]></category>

		<guid isPermaLink="false">http://www.gpgpu.org/cgi-bin/blosxom.cgi/ImageAndVolumeProcessing/krugerVis03.html</guid>
		<description><![CDATA[This Vis03 paper by Krüger and Westermann addresses the integration of early ray termination and empty-space skipping into texture based volume rendering on graphical processing units (GPU). Therefore, volume ray-casting on programmable graphics hardware is described as an alternative to object-order approaches. The early z-test is exploited to terminate fragment processing once sufficient opacity has [...]]]></description>
			<content:encoded><![CDATA[<p>This <a title="VIS 2003" href="http://vis.computer.org/Vis2003/" target="_blank">Vis03</a> paper by <a href="http://wwwcg.in.tum.de/people/Krueger" target="_blank">Krüger</a> and <a href="http://wwwcg.in.tum.de/people/Westermann">Westermann</a> addresses the integration of early ray termination and empty-space skipping into texture based volume rendering on graphical processing units (GPU). Therefore, volume ray-casting on programmable graphics hardware is described as an alternative to object-order approaches. The early z-test is exploited to terminate fragment processing once sufficient opacity has been accumulated, and to skip empty space along the rays of sight. Performance gains up to a factor of 3 for typical renditions of volumetric data sets on the ATI 9700 graphics card are <a href="ftp://wwwcg.in.tum.de/Publications/vis03-rc/vis03-rc.mpg" target="_blank">demonstrated</a>. (<a href="http://wwwcg.in.tum.de/Research/Publications/Raycast" target="_blank">Acceleration Techniques for GPU-based Volume Rendering</a> To appear in <a href="http://vis.computer.org/vis2003/">IEEE Visualization 2003</a>)</p>
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		<slash:comments>0</slash:comments>
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		<title>Fast Volume Segmentation With Simultaneous Visualization Using Programmable Graphics Hardware</title>
		<link>http://gpgpu.org/2003/09/02/fast-volume-segmentation-with-simultaneous-visualization-using-programmable-graphics-hardware</link>
		<comments>http://gpgpu.org/2003/09/02/fast-volume-segmentation-with-simultaneous-visualization-using-programmable-graphics-hardware#comments</comments>
		<pubDate>Tue, 02 Sep 2003 05:22:00 +0000</pubDate>
		<dc:creator>Mark Harris</dc:creator>
				<category><![CDATA[Research]]></category>
		<category><![CDATA[Papers]]></category>
		<category><![CDATA[Volume Rendering]]></category>

		<guid isPermaLink="false">http://www.gpgpu.org/cgi-bin/blosxom.cgi/ImageAndVolumeProcessing/sherbondyVolumeSeg.html</guid>
		<description><![CDATA[This IEEE Visualization 2003 paper by Sherbondy et al. describes a fast approach to segmentation with simultaneous visualization for medical imaging using the GPU. Specifically, their approach iterates a seeded region growing algorithm, where the seeds are dispersed according to a nonlinear diffusion process. An implicit segmentation surface is then defined according to the population [...]]]></description>
			<content:encoded><![CDATA[<p>This IEEE Visualization 2003 paper by Sherbondy et al. describes a fast approach to segmentation with simultaneous visualization for medical imaging using the GPU. Specifically, their approach iterates a seeded region growing algorithm, where the seeds are dispersed according to a nonlinear diffusion process. An implicit segmentation surface is then defined according to the population of the seed volume. This paper also introduces the technique of computational masking, whereby the depth buffer is used to limit computation to an active subvolume. This segmentation algorithm is shown to be 10-20 times faster than an SSE2 optimized CPU version of the algorithm. (<a href="http://graphics.stanford.edu/papers/volseg/" title="Linke to paper" target="_blank">Fast Volume Segmentation With Simultaneous Visualization Using Programmable Graphics Hardware</a>. <a href="http://www.stanford.edu/~sherbond" title="Anthony Sherbondy" target="_blank">Anthony Sherbondy</a>, <a href="http://graphics.stanford.edu/~mhouston/" title="Mike Houston" target="_blank">Mike Houston</a>, <a href="http://rsl.stanford.edu/napel/" title="Sandy Napel" target="_blank">Sandy Napel</a>. To appear in <a href="http://vis.computer.org/vis2003/" target="_blank">IEEE Visualization 2003</a>)</p>
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		<title>Interactive Deformation and Visualization of Level Set Surfaces using Graphics Hardware</title>
		<link>http://gpgpu.org/2003/08/29/interactive-deformation-and-visualization-of-level-set-surfaces-using-graphics-hardware</link>
		<comments>http://gpgpu.org/2003/08/29/interactive-deformation-and-visualization-of-level-set-surfaces-using-graphics-hardware#comments</comments>
		<pubDate>Fri, 29 Aug 2003 21:06:00 +0000</pubDate>
		<dc:creator>Mark Harris</dc:creator>
				<category><![CDATA[Research]]></category>
		<category><![CDATA[Papers]]></category>
		<category><![CDATA[Volume Rendering]]></category>

		<guid isPermaLink="false">http://www.gpgpu.org/cgi-bin/blosxom.cgi/ImageAndVolumeProcessing/lefohnVisLevelSet2003.html</guid>
		<description><![CDATA[This IEEE Visualization 2003 paper by Lefohn et al. describes the computation and visualization of deforming level-set surfaces on a GPU. The paper describes a new technique for efficiently processing the dynamic, sparse volumes encountered in level-set computations. The technique stores a packed representation of the sparse volume on the GPU and performs both the [...]]]></description>
			<content:encoded><![CDATA[<p>This IEEE Visualization 2003 paper by Lefohn et al. describes the computation and visualization of deforming level-set surfaces on a GPU. The paper describes a new technique for efficiently processing the dynamic, sparse volumes encountered in level-set computations. The technique stores a packed representation of the sparse volume on the GPU and performs both the level-set computation and real-time volume rendering on this packed format. The new level-set solver is shown to be 10-15 times faster than an optimized CPU implementation. The paper demonstrates the new algorithm with a volume segmentation application. (<a href="http://www.sci.utah.edu/~lefohn/work/rls/visLevelSet/" title="Link to paper" target="_blank">Interactive Deformation and Visualization of Level Set Surfaces using Graphics Hardware</a>.<a href="http://www.sci.utah.edu/~lefohn/" title="Aaron Lefohn" target="_blank"> Aaron E. Lefohn</a>, <a href="http://www.cs.utah.edu/~jmk/" title="Joe Kniss" target="_blank">Joe M. Kniss</a>, <a href="http://www.sci.utah.edu/personnel/hansen" title="Chuck Hansen" target="_blank">Charles D. Hansen</a> and <a href="http://www.sci.utah.edu/personnel/whitaker.html" title="Ross Whitaker" target="_blank">Ross T. Whitaker</a>. To appear in <a href="http://vis.computer.org/vis2003/" title="IEEE Vis" target="_blank">IEEE Visualization 2003</a>.)</p>
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