Adapting the storage of large medical datasets to enable interactive display

In this paper, we present an interactive out-of-core volume data exploration approach which has been developed to augment the existing capabilities of the LhpBuilder software, a core component of the ongoing European project LHDL [1]. The requirements relate to importing, accessing, visualising 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 visualisation 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. Experimental results show that the user can interactively explore large volume datasets such as the Visible Human male (1760×1024×1878, with a file size of 3.15 GB) on a commodity graphics platform, with ease.