Title:	A FLEXIBLE FRAMEWORK FOR MULTI-VOLUME DATA VISUALIZATION
Author(s):	Nikolay Gavrilov, Alexandra Belokamenskaya, Vadim Turlapov
ISBN:	978-972-8939-48-9
Editors:	Yingcai Xiao
Year:	2011
Edition:	Single
Keywords:	GPGPU, raycasting, multi-volume rendering, medical visualization.
Type:	Poster/Demonstration
First Page:	337
Last Page:	339
Language:	English
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Paper Abstract:	In this paper we present a framework for visualization of three-dimensional multiple volumetric datasets. We use such optimization strategies for GPU-based raycasting as the early ray termination and empty space skipping. An SMV (Stereo Multi-volume Viewer) provides such visualization techniques as Direct Volume Rendering via 1D- or 2D- transfer functions, multiple semi-transparent discrete isosurfaces, MIP, MIDA, etc. We also use random ray start position generation and further frames accumulation in order to reduce visual artifacts. The quality can be also improved by GPU-based volumetric tri-cubic up-sampling of the source datasets or by on-the-fly tri-cubic filtering during the rendering process. In addition to the clipping bounding box, user can use custom bounding mesh for more accurate region-of-interest selection. The SMV also supports 4 different stereoscopic visualization modes. We outlined the visualization performance in terms of frame rates for different visualization techniques on several graphic cards.
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