The Journal of Supercomputing

, Volume 51, Issue 1, pp 3–19 | Cite as

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

  • Anupam Agrawal
  • Josef Kohout
  • Gordon J. Clapworthy
  • Nigel J. B. McFarlane
  • Feng Dong
  • Marco Viceconti
  • Fulvia Taddei
  • Debora Testi
Article

Abstract

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 

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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Anupam Agrawal
    • 1
  • Josef Kohout
    • 1
  • Gordon J. Clapworthy
    • 1
  • Nigel J. B. McFarlane
    • 1
  • Feng Dong
    • 1
  • Marco Viceconti
    • 2
  • Fulvia Taddei
    • 2
  • Debora Testi
    • 3
  1. 1.Department of Computer Science & TechnologyUniversity of BedfordshireLutonUK
  2. 2.Laboratorio di Tecnologia MedicaIstituto Ortopedico RizzoliBolognaItaly
  3. 3.BioComputing Competence CentreSCSCasalecchio di RenoItaly

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