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Enabling the interactive display of large medical volume datasets by multiresolution bricking

机译:通过多分辨率砌块启用大型医疗数据集的交互式显示

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In this paper, we present an approach to interactive out-of-core volume data exploration that has been developed to augment the existing capabilities of the LhpBuilder software, a core component of the European project LHDL (http://www.biomedtown.org/biomed_town/lhdl). The requirements relate to importing, accessing, visualizing and extracting a part of a very large volume dataset by interactive visual exploration. Such datasets contain billions of voxels and, therefore, several gigabytes are required just to store them, which quickly surpass the virtual address limit of current 32-bit PC platforms. We have implemented a hierarchical, bricked, partition-based, out-of-core strategy to balance the usage of main and external memories. A new indexing scheme is introduced, which permits the use of a multiresolution bricked volume layout with minimum overhead and also supports fast data compression. Using the hierarchy constructed in a pre-processing step, we generate a coarse approximation that provides a preview using direct volume visualization for large-scale datasets. A user can interactively explore the dataset by specifying a region of interest (ROI), which further generates a much more accurate data representation inside the ROI. If even more precise accuracy is needed inside the ROI, nested ROIs are used. The software has been constructed using the Multimod Application Framework, a VTK-based system; however, the approach can be adopted for the other systems in a straightforward way. Experimental results show that the user can interactively explore large volume datasets such as the Visible Human Male/Female (with file sizes of 3.15/12.03 GB, respectively) on a commodity graphics platform, with ease. Keywords Medical visualization - Large volume data sets - Out-of-core processing - Multiresolution bricking - VTK
机译:在本文中,我们介绍了一种交互式的核心外批量数据探索方法,该方法已开发用于增强LhpBuilder软件的现有功能,该软件是欧洲项目LHDL的核心组件(http://www.biomedtown.org / biomed_town / lhdl)。这些要求涉及通过交互式视觉探索来导入,访问,可视化和提取非常大量的数据集的一部分。这样的数据集包含数十亿个体素,因此仅存储它们就需要数GB的数据,这很快超过了当前32位PC平台的虚拟地址限制。我们已经实现了分层的,基于块的,基于分区的核心外策略,以平衡主存储器和外部存储器的使用。引入了一种新的索引方案,该方案允许以最小的开销使用多分辨率的块状卷布局,并且还支持快速数据压缩。使用在预处理步骤中构造的层次结构,我们生成了一个粗略的近似值,它使用直接体积可视化为大型数据集提供了预览。用户可以通过指定感兴趣区域(ROI)来交互式地浏览数据集,从而进一步在ROI内部生成更准确的数据表示。如果在ROI内需要更高的精确度,则使用嵌套的ROI。该软件是使用Multimod应用程序框架(基于VTK的系统)构建的。但是,该方法可以直接用于其他系统。实验结果表明,用户可以轻松地在商品图形平台上交互式浏览大量数据集,例如“可见人类”的“男性/女性”(文件大小分别为3.15 / 12.03 GB)。关键字医学可视化-大数据集-核外处理-多分辨率砌块-VTK

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