Efficient CT Image Volume Rendering for Diagnosis
Commenced in January 2007
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Efficient CT Image Volume Rendering for Diagnosis

Authors: HaeNa Lee, Sun K. Yoo

Abstract:

Volume rendering is widely used in medical CT image visualization. Applying 3D image visualization to diagnosis application can require accurate volume rendering with high resolution. Interpolation is important in medical image processing applications such as image compression or volume resampling. However, it can distort the original image data because of edge blurring or blocking effects when image enhancement procedures were applied. In this paper, we proposed adaptive tension control method exploiting gradient information to achieve high resolution medical image enhancement in volume visualization, where restored images are similar to original images as much as possible. The experimental results show that the proposed method can improve image quality associated with the adaptive tension control efficacy.

Keywords: Tension control, Interpolation, Ray-casting, Medical imaging analysis.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1077511

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References:


[1] U.Tiede, T. Schiemann and K. H. Hohne, "Hifh Quality Rendering of Attributed Volume Data," IEEE Visualization, North Carolina, USA, Oct. 1998, pp.255-262.
[2] W. Schroeder, K. Martin and B. Lorensen, The Visualization Toolkit An Object-Oriented Approach to 3D Graphics, New Jersey: Prentice-Hall Inc., 2006, ch. 7.
[3] C. Rossl, F. Zeilfelder, G. Numberger and H. Seidel, "Reconstruction of Volume Data with Quadratic Super Splines," IEEE Transactions on visualization and Computer Graphics, Vol. 10, No. 4, 2004, pp. 397-409.
[4] Byeonghun Lee, Jihye Yun, Jinwook Seo, Byonghyo Shim, Yeong-Gil Shin and Bohyoung Kim, "Fast High-Quality Volume Ray-Casting with Virtual Samplings," IEEE Transactions on visualization and computer graphics, Vol. 16, No. 6, 2010, pp. 1525-1532.
[5] K. Engel, M. Hadwiger, J. M. Kniss, A. E. Lefohn, C. R. Salama and D. Weiskopf, "Real-Time Volume Graphics," SIGGRAPH2004 Course Notes, Los Angeles, USA, Aug. 2004, pp. 1-266.
[6] S. Molnar, 1991, Efficient Supersampling Antialiasing for High-Performance Architectures, UNC-Dc Tech, rep, TR91-023.
[7] E. H. W. Meijering, W. J. Niessen, M. A. Viergever, "Quantitative evaluation of convolution-based methods for medical image interpolation," Vol. 5, No. 2, 2001, pp. 111-126.
[8] C. Zhang, P. Xi and C. Zhang, "CUDA-based Volume Ray-Casting Using Cubic B-spline," 2011 International Conference on Virtual Reality and Visualization(ICVRV), Beijing, China, Nov. 2011, pp. 84-88.
[9] W. Burger, M. J. Burge, Digital Image Processing An Algorithmic Introduction Using Java, New York: Springer, 2007, ch. 16.
[10] I. Drnasin, M. Grgic, "The Use of Mobile Phones in Radiology," ELMAR, 2010 proceedings, Zadar, Croatia, Sept. 2010, pp. 17-21.
[11] M. Levoy, "Display of Surfaces from Volume Data," Vol. 8, No. 3, 1988, pp. 29-37.
[12] C. Yuksel, S. Schaefer, J. Keyser, "On the parameterization of Catmull-Rom curves." Proceedings of ACM Joint Conference on Geometric and Physical Modeling, New York, USA, 2009, pp. 47-53.