ABSTRACT
Transfer function (TF) in direct volume rendering serves to identify and emphasize features of interest (FOIs) and their contextual and regional information for improved visualization. Conventional TF design is not intuitive and usually a 'trial-and-error' process for most users. In an intensity-based one-dimensional (1D) histogram TF, for example, a user needs to repetitively adjust intensity ranges (to identify FOIs) and then assign color and opacity values to the selected range (to emphasize FOIs). In this paper, we propose an intuitive sketch-based interaction technique to design TFs. Our technique enables the user to identify FOIs along the user's viewing ray, with the aid of contextual and regional labels automatically derived from two-dimensional (2D) image slices reconstructed from the ray. For FOI identification, the user makes a sketch on the 2D image slice. Our technique automatically generates an intensity-based 1D TF where the opacity and color values of the intensity range for the FOIs are derived according to their distance from the user's viewpoint and this allows all FOIs along the ray to be visible at once. We show the capabilities of our technique with visualizations on different volumetric data sets, and highlight its advantages when compared to the conventional histogram TF design.
- Fuchs, R., and Hauser, H. 2009. Visualization of Multi-Variate Scientific Data. Comput. Graph. Forum., 1670--90.Google Scholar
- Max, N. 2005. Progress in scientific visualization. Visual. Comput. 21, 12, 979--84.Google ScholarCross Ref
- Kniss, J., Kindlmann, G., and Hansen, C. 2001. Interactive volume rendering using multi-dimensional transfer functions and direct manipulation widgets. Proc. Visualization, 255--62. Google ScholarDigital Library
- Caban, J., and Rheingans, P. 2008. Texture-based transfer functions for direct volume rendering. IEEE T. Vis.Comput. 14, 6, 1364--71. Google ScholarDigital Library
- Correa, C., and Ma, K.-L. 2008. Size-based transfer functions: A new volume exploration technique. IEEE T. Vis.Comput. 14, 6, 1380--7. Google ScholarDigital Library
- Correa, C., and Ma, K.-L. 2011. Visibility histograms and visibility-driven transfer functions. IEEE T. Vis.Comput. 17, 2, 192--204. Google ScholarDigital Library
- Jung, Y., Kim, J., Eberl, S., Fulham, M., and Feng, D. D. 2013. Visibility-driven PET-CT visualisation with region of interest (ROI) segmentation. Visual. Comput. 29, 6--8, 805--15. Google ScholarDigital Library
- Ropinski, T., Praßni, J., Steinicke, F., and Hinrichs, K. H. 2008. Stroke-Based Transfer Function Design. Proc. Volume Graphics, 41--8. Google ScholarDigital Library
- Guo, H., Mao, N., and Yuan, X., 2011. Wysiwyg (what you see is what you get) volume visualization. IEEE T. Vis.Comput. 17, 12, 2106--14. Google ScholarDigital Library
- Shen, E., Li, S., Cai, X., Zeng, L., and Wang, W. 2014. Sketch-based interactive visualization: a survey. J. Visual-japan. 17, 4, 275--94. Google ScholarDigital Library
- He, T., Hong, L., Kaufman, A., and Pfister, H. 1996. Generation of transfer functions with stochastic search techniques. Proc. Visualization., 227--34. Google ScholarDigital Library
- Tzeng, F.-Y., Lum, E. B., and Ma, K.-L. 2003. A novel interface for higher-dimensional classification of volume data. Proc. Visualization, 66. Google ScholarDigital Library
- Huang, R., and Ma, K.-L. 2003. Rgvis: Region growing based techniques for volume visualization. Proc. PCCGA., 355--63. Google ScholarDigital Library
- (31.03.2016). DICOM Sample image sets. Available: http://www.osirix-viewer.com/datasets/Google Scholar
- Li, Z., Wu, X.-M., and Chang, S.-F. 2012. Segmentation using superpixels: A bipartite graph partitioning approach. Proc. CVPR., 789--96. Google ScholarDigital Library
- Lanckriet, G. R., Cristianini, N., Bartlett, P., Ghaoui, L. E., and Jordan, M. I. 2004. Learning the kernel matrix with semidefinite programming. J. Mach. Learn. Res. 5, 27--72. Google ScholarDigital Library
- Optiz, D., and Maclin, R. 1999. Popular ensemble methods: An empirical study. J. Artif. Intell. Res., 169--98.Google Scholar
- Comaniciu, D., and Meer, P. 2002. Mean shift: A robust approach toward feature space analysis. IEEE T. Pattern. Anal. 24, 5, 603--19. Google ScholarDigital Library
- Felzenszwalb, P. F., and Huttenlocher, D. P. 2002. Efficient graph-based image segmentation. Int. J. Comput. Vision. 59, 2, 167--81. Google ScholarDigital Library
- Ng, A. Y., Jordan, M. I., and Weiss, Y. 2002. On spectral clustering: Analysis and an algorithm. Adv. Neur. In. 2, 849--56.Google Scholar
- Harrower, M., and Brewer, C. A. 2003. ColorBrewer. org: an online tool for selecting colour schemes for maps. The Cartographic Journal 40, 1, 27--37.Google ScholarCross Ref
- (31.03.2016). The Volume Library. Available: http://schorsch.efi.fh-nuernberg.de/data/volume/Google Scholar
- Meyer-Spradow, J., Ropinski, T., Mensmann, J., and Hinrichs, K. 2009. Voreen: A rapid-prototyping environment for ray-casting-based volume visualizations. IEEE Comput. Graph. 29, 6, 6--13.Google ScholarDigital Library
- An intuitive Sketch-based Transfer Function Design via Contextual and Regional Labelling
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