Abstract
In this paper, we present a novel viewpoint selection framework for angiographic volume data. We propose several view descriptors based on typical concerns of clinicians for the view evaluation. Compared with conventional approaches, our method can deliver a more representative global optimal view by sampling at a much higher rate in the view space. Instead of performing analysis on sample views individually, we construct a solution space to estimate the quality of the views. Descriptor values are propagated to the solution space where an efficient searching process can be performed. The best viewpoint can be found by analyzing the accumulated descriptor values in the solution space based on different visualization goals.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Polonsky, O., Patanè, G., Biasotti, S., Gotsman, C., Spagnuolo, M.: What’s in an image? The Visual Computer 21, 840–847 (2005)
Blanz, V., Tarr, M., Bulthoff, H.: What object attributes determine canonical views? Perception, 579–599 (1999)
Kumar, S., Manocha, D., Garrett, B., Lin, M.: Hierarchical back-face culling. In: 7th Eurographics Workshop on Rendering, pp. 231–240 (1996)
Kamada, T., Kawai, S.: A simple method for computing general position in displaying three-dimensional objects. In: Comp. Vis. Graph. Image Proc., vol. 41, pp. 43–56 (1988)
Vázquez, P., Feixas, M., Sbert, M., Heidrich, W.: Automatic view selection using viewpoint entropy and its application to image-based modelling. Computer Graphics Forum 22, 689–700 (2004)
Vázquez, P., Feixas, M., Sbert, M., Heidrich, W.: Viewpoint selection using viewpoint entropy. In: Vision Modeling and Visualization Conference, pp. 273–280 (2001)
Page, D.L., Koschan, A., Sukumar, S.R., Roui-Abidi, B., Abidi, M.A.: Shape analysis algorithm based on information theory. In: ICIP (1), pp. 229–232 (2003)
Sbert, M., Plemenos, D., Feixas, M., Gonzalez, F.: Viewpoint quality: Measures and applications. In: Computational Aesthetics in Graphics, Visualization and Imaging, pp. 185–192 (2005)
Lee, C.H., Varshney, A., Jacobs, D.: Mesh saliency. ACM Transactions on Graphics 24, 659–666 (2005)
Bordoloi, U., Shen, H.W.: View selection for volume rendering. In: IEEE Visualization, pp. 487–494 (2005)
Takahashi, S., Fujishiro, I., Takeshima, Y., Nishita, T.: A feature-driven approach to locating optimal viewpoints for volume visualization. In: IEEE Visualization, pp. 495–502 (2005)
Pommert, A., Bomans, M., Hohne, K.H.: Volume visualization in magnetic resonance angiography. IEEE Computer Graphics and Applications 12, 12–13 (1992)
Chan, M.Y., Wu, Y., Qu, H., Chung, A.C.S., Wong, W.C.K.: Mip-guided vascular image visualization with multi-dimensional transfer function. In: Computer Graphics International, pp. 372–384 (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Chan, MY., Qu, H., Wu, Y., Zhou, H. (2006). Viewpoint Selection for Angiographic Volume. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2006. Lecture Notes in Computer Science, vol 4291. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11919476_53
Download citation
DOI: https://doi.org/10.1007/11919476_53
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-48628-2
Online ISBN: 978-3-540-48631-2
eBook Packages: Computer ScienceComputer Science (R0)