Hierarchical volume visualization of brain anatomy

Jean Paul Balabanian, Martin Ystad, Ivan Viola, Arvid Lundervold, Helwig Hauser, Eduard Gröller

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Scientific data-sets often come with an inherent hierarchical structure such as functional substructures within organs. In this work we propose a new visualization approach for volume data which is augmented by the explicit representation of hierarchically structured data. The volumetric structures are organized in an interactive hierarchy view. Seamless zooming between data visualization, with volume rendering, and map viewing, for orientation and navigation within the hierarchy, facilitates deeper insight on multiple levels. The map shows all structures, organized in multiple hierarchy levels. Focusing on a selected node allows a visual analysis of a substructure as well as identifying its location in the hierarchy. The visual style of the node in focus, its parent and child nodes are automatically adapted during interaction to emphasize the embedding in the hierarchy. The hierarchy view is linked to a traditional tree view. The value of this new visualization approach is demonstrated on segmented MRI brain data consisting of hundreds of cortical and sub-cortical structures.

Original languageEnglish (US)
Title of host publication13th International Fall Workshop Vision, Modeling, and Visualization 2008, VMV 2008
Pages313-322
Number of pages10
StatePublished - Dec 1 2008
Event13th International Fall Workshop Vision, Modeling, and Visualization 2008, VMV 2008 - Konstanz, Germany
Duration: Oct 8 2008Oct 10 2008

Publication series

Name13th International Fall Workshop Vision, Modeling, and Visualization 2008, VMV 2008

Conference

Conference13th International Fall Workshop Vision, Modeling, and Visualization 2008, VMV 2008
CountryGermany
CityKonstanz
Period10/8/0810/10/08

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Modeling and Simulation

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