Information
- Publication Type: Technical Report
- Workgroup(s)/Project(s):
- Date: December 2008
- Number: TR-186-2-08-14
Abstract
This paper presents two techniques for the linking of 2D and 3D views in medical applications. Hereby, the goal is a better integration of 3D volume visualization into the diagnostic workflow. Until now, the main obstacle for a good integration is the time-consuming process to adjust various parameters. The LiveSync interaction metaphor is a new concept to synchronize 2D slice views and 3D volumetric views of medical data sets. A single intuitive picking interaction on anatomical structures which are detected in 2D slices results in an automatically generated 3D view. To further improve the integration contextual picking is presented as a method for the interactive identification of contextual interest points within volumetric data. Our results demonstrate how these techniques improve the efficiency to generate diagnostically relevant images and how contextual interest points can, e.g., facilitate the highlighting of relevant structures.Additional Files and Images
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@techreport{TR-186-2-08-14, title = "Smart Linking of 2D and 3D Views in Medical Applications", author = "Peter Kohlmann and Stefan Bruckner and Armin Kanitsar and Eduard Gr\"{o}ller", year = "2008", abstract = "This paper presents two techniques for the linking of 2D and 3D views in medical applications. Hereby, the goal is a better integration of 3D volume visualization into the diagnostic workflow. Until now, the main obstacle for a good integration is the time-consuming process to adjust various parameters. The LiveSync interaction metaphor is a new concept to synchronize 2D slice views and 3D volumetric views of medical data sets. A single intuitive picking interaction on anatomical structures which are detected in 2D slices results in an automatically generated 3D view. To further improve the integration contextual picking is presented as a method for the interactive identification of contextual interest points within volumetric data. Our results demonstrate how these techniques improve the efficiency to generate diagnostically relevant images and how contextual interest points can, e.g., facilitate the highlighting of relevant structures.", month = dec, number = "TR-186-2-08-14", address = "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria", institution = "Institute of Computer Graphics and Algorithms, Vienna University of Technology ", note = "human contact: technical-report@cg.tuwien.ac.at", URL = "https://www.cg.tuwien.ac.at/research/publications/2008/TR-186-2-08-14/", }