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. If even more precise accuracy is needed inside the ROI, nested ROIs are used. 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. 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 new indexing scheme is introduced, which permits the use of a multiresolution bricked volume layout with minimum overhead and also supports fast data compression. We have implemented a hierarchical, bricked, partition-based, out-of-core strategy to balance the usage of main and external memories. 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.

The requirements relate to importing, accessing, visualizing and extracting a part of a very large volume dataset by interactive visual exploration.

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 ().

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