journal article·2014-01Open access

GPU Accelerating Technique for Rendering Implicitly Represented Vasculatures

Qingqi Hong, Beizhan Wang, Qingde Li, Yan Li, Qingqiang Wu

Abstract

With the flooding datasets of medical Computed Tomography (CT) and Magnetic Resonance Imaging (MRI), implicit modeling techniques are increasingly applied to reconstruct the human organs, especially the vasculature. However, displaying implicitly represented geometric objects arises heavy computational burden. In this study, a Graphics Processing Unit (GPU) accelerating technique was developed for high performance rendering of implicitly represented objects, especially the vasculatures. The experimental results suggested that the rendering performance was greatly enhanced via exploiting the advantages of modern GPUs.
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Research context

OpenAlex topics: Computer Graphics and Visualization Techniques · Medical Image Segmentation Techniques · 3D Shape Modeling and Analysis

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Affiliations

Software School, Xiamen University, Xiamen, 361005, China

Department of Computer Science, University of Hull, HU6 7RX, Hull, UK

School of Management, Xiamen University, Xiamen, 361005, China

References

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