网格计算环境下医疗数据集的可视化管道

Aboamama Atahar Ahmed, M. S. Latiff, K. A. Bakar, Z. Rajion
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引用次数: 12

摘要

大型数据集的远程可视化通常采用远程查看和存储静态图像的缩放技术。然而,随着数据集规模和可视化操作的不断增加,导致传统台式计算机的性能不足。此外,诸如isosurface之类的可视化技术依赖于运行机器的可用资源和数据集的大小。此外,对强大计算能力的不断需求和数据集规模的不断增加,导致对网格计算基础设施的迫切需求。然而,在当前的网格中出现了一些问题,例如客户端机器上的资源可用性不足以处理大型数据集。最重要的是,可视化管道组件之间不同的输出设备和不同的网络带宽常常导致输出适合一台机器而不适合另一台机器。本文研究了如何利用网格服务来支持大型数据集的远程可视化,并通过应用网格计算技术来打破资源物理共址的限制。我们展示了我们的网格支持架构,以可视化大型医疗数据集(大约500万个多边形),用于在资源有限的客户端上进行远程交互式可视化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Visualization Pipeline for Medical Datasets on Grid Computing Environment
Distance visualization of large datasets often takes the direction of remote viewing and zooming techniques of stored static images. However, the continuous increase in the size of datasets and visualization operation causes insufficient performance with traditional desktop computers. Additionally, the visualization techniques such as isosurface depend on the available resources of the running machine and the size of datasets. Moreover, the continuous demand for powerful computing powers and continuous increase in the size of datasets results an urgent need for a grid computing infrastructure. However, some issues arise in current grid such as resources availability at the client machines which are not sufficient enough to process large datasets. On top of that, different output devices and different network bandwidth between the visualization pipeline components often result output suitable for one machine and not suitable for another. In this paper we investigate how the grid services could be used to support remote visualization of large datasets and to break the constraint of physical co-location of the resources by applying the grid computing technologies. We show our grid enabled architecture to visualize large medical datasets (circa 5 million polygons) for remote interactive visualization on modest resources clients.
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