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Hierarchical Volume Visualization of Brain Anatomy

J. Balabanian, M. Ystad, I. Viola, A. Lundervold, H. Hauser, and M. E. Gröller

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.

J. Balabanian, M. Ystad, I. Viola, A. Lundervold, H. Hauser, and M. E. Gröller, "Hierarchical Volume Visualization of Brain Anatomy," in Proceeding of Vision, Modeling and Visualization (VMV 2008), 2008, p. 313–322.
[BibTeX]

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