This Article 
 Bibliographic References 
 Add to: 
LiveSync: Deformed Viewing Spheres for Knowledge-Based Navigation
November/December 2007 (vol. 13 no. 6)
pp. 1544-1551
Although real-time interactive volume rendering is available even for very large data sets, this visualization method is used quite rarely in the clinical practice. We suspect this is because it is very complicated and time consuming to adjust the parameters to achieve meaningful results. The clinician has to take care of the appropriate viewpoint, zooming, transfer function setup, clipping planes and other parameters. Because of this, most often only 2D slices of the data set are examined. Our work introduces LiveSync, a new concept to synchronize 2D slice views and volumetric views of medical data sets. Through intuitive picking actions on the slice, the users define the anatomical structures they are interested in. The 3D volumetric view is updated automatically with the goal that the users are provided with expressive result images. To achieve this live synchronization we use a minimal set of derived information without the need for segmented data sets or data-specific pre-computations. The components we consider are the picked point, slice view zoom, patient orientation, viewpoint history, local object shape and visibility. We introduce deformed viewing spheres which encode the viewpoint quality for the components. A combination of these deformed viewing spheres is used to estimate a good viewpoint. Our system provides the physician with synchronized views which help to gain deeper insight into the medical data with minimal user interaction.

[1] V. Blanz, M. J. Tarr, and H. H. Bülthoff, What object attributes determine canonical views? Perception 28 (5): 575–599, 1999.
[2] U. D. Bordoloi and H.-W. Shen, View selection for volume rendering. In Proceedings of IEEE Visualization 2005, pages 487–494, 2005.
[3] P. Bourke, Distributing Points on a Sphere. Available online at spherepoints/, March 2007.
[4] M.-Y. Chan, H. Qu, Y. Wu, and H. Zhou, Viewpoint selection for angiographic volume. In Proceedings of the Second International Symposium on Visual Computing 2006, pages 528–537, 2006.
[5] S. Fleishman, D. Cohen-Or, and D. Lischinski, Automatic camera placement for image-based modeling. Computer Graphics Forum, 19 (2): 101–110, 2000.
[6] C. H. Lee, A. Varshney, and D.W. Jacobs, Mesh saliency. In Proceedings of ACM SIGGRAPH 2005, pages 659–666, 2005.
[7] K. Mühler, M. Neugebauer, C. Tietjen, and B. Preim, Viewpoint selection for intervention planning. In Proceedings of Eurographics/IEEE VGTC Symposium on Visualization 2007, pages 267–274, 2007.
[8] S. Owada, F. Nielsen, and T. Igarashi, Volume catcher. In Proceedings of ACM Symposium on Interactive 3D Graphics and Games 2005, pages 111–116, 2005.
[9] O. Polonsky, G. Patané, S. Biasotti, C. Gotsman, and M. Spagnuolo, What's in an image: Towards the computation of the 'best' view of an object. The Visual Computer, 21 (8–10): 840–847, 2005.
[10] Y. Sato, C.-F. Westin, A. Bhalerao, S. Nakajima, N. Shiraga, S. Tamura, and R. Kikinis, Tissue classification based on 3D local intensity structures for volume rendering. IEEE Transactions on Visualization and Computer Graphics, 6 (2): 160–180, 2000.
[11] M. Sbert, D. Plemenos, M. Feixas, and F. González, Viewpoint quality: Measures and applications. In Proceedings of Computational Aesthetics in Graphics, Visualization and Imaging 2005, pages 185–192, 2005.
[12] S. Takahashi, I. Fujishiro, Y. Takeshima, and T. Nishita, A feature-driven approach to locating optimal viewpoints for volume visualization. In Proceedings of IEEE Visualization 2005, pages 495–502, 2005.
[13] M. Tory and C. Swindells, Comparing ExoVis, orientation icon, and in-place 3D visualization techniques. In Proceedings of Graphics Interface 2003, pages 57–64, 2003.
[14] J. M. van Verth and L. M. Bishop, Essential Mathematics for Games and Interactive Applications: A Programmer's Guide. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, 2004.
[15] P.-P. Vázquez, M. Feixas, M. Sbert, and W. Heidrich, Viewpoint selection using viewpoint entropy. In Proceedings of Vision, Modeling, and Visualization 2001, pages 273–280, 2001.
[16] P.-P. Vázquez, M. Feixas, M. Sbert, and W. Heidrich, Automatic view selection using viewpoint entropy and its application to image-based modelling. Computer Graphics Forum, 22 (4): 689–700, 2003.
[17] I. Viola, M. Feixas, M. Sbert, and M. E. Gröller, Importance-driven focus of attention. IEEE Transactions on Visualization and Computer Graphics, 12 (5): 933–940, 2006.
[18] Virtual Terrain Project. Spherical Textures. Available online at , March 2007.
[19] E. Williams, Aviation Formulary V1.43. Available online at, March 2007.
[20] J. Zhou, M. Hinz, and K. D. Tönnies, Focal region-guided feature-based volume rendering. In Proceedings of the 1st International Symposium on 3D Data Processing, Visualization, and Transmission 2002, pages 87–90, 2002.

Index Terms:
Navigation, interaction, linked views, medical visualization, viewpoint selection.
Peter Kohlmann, Stefan Bruckner, Armin Kanitsar, Eduard Gröller, "LiveSync: Deformed Viewing Spheres for Knowledge-Based Navigation," IEEE Transactions on Visualization and Computer Graphics, vol. 13, no. 6, pp. 1544-1551, Nov.-Dec. 2007, doi:10.1109/TVCG.2007.70576
Usage of this product signifies your acceptance of the Terms of Use.