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GPU-based object-order ray-casting for large datasets

  • Stony Brook University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

24 Scopus citations

Abstract

We propose a GPU-based object-order ray-casting algorithm for the rendering of large volumetric datasets, such as the Visible Human CT datasets. A volumetric dataset is decomposed into small sub-volumes, which are then organized using a min-max octree structure. The small sub-volumes are stored in the leaf nodes of the min-max octree, which are also called cells. The cells are classified using a transfer function, and the visible cells are then loaded into the video memory or the AGP memory. The cells are sorted and projected onto the image plane front to back. The cell projection is implemented using a volumetric ray-casting algorithm on the GPU, In order to make the cell projection more efficient, we devise a propagation method to sort cells into layers. The cells within the same layer are projected at the same time. We demonstrate the efficiency of our algorithm using the Visible Human datasets and a segmented photographic brain dataset on commodity PCs.

Original languageEnglish
Title of host publicationVolume Graphics 2005 Eurographics/IEEE VGTC Workshop Proceedings - Fourth International Workshop on Volume Graphics
Pages177-185
Number of pages9
StatePublished - 2005
EventFourth International Workshop on Volume Graphics 2005 - Stony Brook, NY, United States
Duration: Jun 20 2005Jun 21 2005

Publication series

NameVolume Graphics 2005 Eurographics/IEEE VGTC Workshop Proceedings - Fourth International Workshop on Volume Graphics

Conference

ConferenceFourth International Workshop on Volume Graphics 2005
Country/TerritoryUnited States
CityStony Brook, NY
Period06/20/0506/21/05

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