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GPU-based focus-driven multi-coordinates viewing system for large volume data visualisation

机译:基于GPU的焦点驱动的多坐标查看系统,可实现大数据可视化

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摘要

In this paper, we are presenting a generalised contactless interactive graphics processing unit (GPU) accelerated compute unified device architecture (CUDA) based focus and context visualisation approach with displaying the inner anatomy of the large scale visible human male dataset in multi-coordinate viewing system (MCVS). The focusing area has been achieved by 3D Cartesian region of interest (ROI). The large dataset has been structured by using Octree method. The volume rendering part has been done by using an improved ray intersection cube method for voxels with the ray casting algorithm. The final results would allow the doctors to diagnose and analyse the atlas of 8-bit CT-scan data visualisation with efficient frame rates of rendering speed. The system is tested on ten multiple sized of 3D medical datasets ranging from 10 MB to 3.15 GB. The scope of this system is to explore of the human body for surgery purpose.
机译:在本文中,我们将提出一种基于通用和非接触式交互式图形处理单元(GPU)加速计算统一设备架构(CUDA)的焦点和上下文可视化方法,以在多坐标查看系统中显示大规模可见人类男性数据集的内部解剖结构(MCVS)。聚焦区域已通过3D笛卡尔感兴趣区域(ROI)实现。大型数据集已使用Octree方法构造。通过使用带有射线投射算法的改进的体素射线相交立方体方法完成了体绘制部分。最终结果将使医生能够以有效的渲染速度帧速率诊断和分析8位CT扫描数据可视化图集。该系统在10个大小从10 MB到3.15 GB的多种尺寸的3D医学数据集上进行了测试。该系统的范围是为了手术目的探索人体。

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