Hierarchical Volume Visualization of Brain Anatomy

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

INPROCEEDINGS, October 2008, Konstanz, Germany

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.

Published

Proceeding of Vision, Modeling and Visualization (VMV 2008)

Media

BibTeX

@inproceedings{balabanian08hierarchical,
  title =      "Hierarchical Volume Visualization of Brain Anatomy",
  author =     "Jean-Paul Balabanian and Martin Ystad and Ivan Viola and
               Arvid Lundervold and Helwig Hauser and M. Eduard
               Gr{\"o}ller",
  year =       "2008",
  pages =      "313--322",
  month =      {oct},
  booktitle =  "Proceeding of Vision, Modeling and Visualization (VMV 2008)",
  isbn =       "978-3-89838-609-8",
  location =   "Konstanz, Germany",
  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.},



}