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Gordon Kindlmann, David Weinstein, David Hart, "Strategies for Direct Volume Rendering of Diffusion Tensor Fields," IEEE Transactions on Visualization and Computer Graphics, vol. 6, no. 2, pp. 124138, AprilJune, 2000.  
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@article{ 10.1109/2945.856994, author = {Gordon Kindlmann and David Weinstein and David Hart}, title = {Strategies for Direct Volume Rendering of Diffusion Tensor Fields}, journal ={IEEE Transactions on Visualization and Computer Graphics}, volume = {6}, number = {2}, issn = {10772626}, year = {2000}, pages = {124138}, doi = {http://doi.ieeecomputersociety.org/10.1109/2945.856994}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
RefWorks Procite/RefMan/Endnote  x  
TY  JOUR JO  IEEE Transactions on Visualization and Computer Graphics TI  Strategies for Direct Volume Rendering of Diffusion Tensor Fields IS  2 SN  10772626 SP124 EP138 EPD  124138 A1  Gordon Kindlmann, A1  David Weinstein, A1  David Hart, PY  2000 KW  Volume rendering KW  diffusion tensor KW  tensor visualization KW  barycentric coordinates KW  anisotropy KW  transfer function KW  reactiondiffusion texture KW  tensor interpolation. VL  6 JA  IEEE Transactions on Visualization and Computer Graphics ER   
Abstract—Diffusionweighted magnetic resonance imaging is a relatively new modality capable of elucidating the fibrous structure of certain types of tissue, such as the white matter within the brain. One tool for interpreting this data is volume rendering because it permits the visualization of three dimensional structure without a prior segmentation process. In order to use volume rendering, however, we must develop methods for assigning opacity and color to the data, and create a method to shade the data to improve the legibility of the rendering. Previous work introduced three such methods: barycentric opacity maps, hueballs (for color), and littensors (for shading). The current paper expands on and generalizes these methods, describing and demonstrating further means of generating opacity, color, and shading from the tensor information. We also propose anisotropic reactiondiffusion volume textures as an additional tool for visualizing the structure of diffusion data. The patterns generated by this process can be visualized on their own or they can be used to supplement the volume rendering strategies described in the rest of the paper. Finally, because interpolation between data points is a fundamental issue in volume rendering, we conclude with a discussion and evaluation of three distinct interpolation methods suitable for diffusion tensor MRI data.
[1] D.C. Banks, “Illumination in Diverse Codimensions,” Proc. SIGGRAPH 94, vol. 28, pp. 327334, 1994.
[2] P.J. Basser, J. Mattiello, and D. Le Bihan, “Estimation of the Effective SelfDiffusion Tensor from the NMR SpinEcho,” Magnetic Resonance, vol. 103, pp. 247254, 1994.
[3] P.J. Basser and C. Pierpaoli, “A Simplified Method to Measure the Diffusion Tensor from Seven MR Images,” Magnetic Resonance in Medicine, vol. 39, pp. 928934, 1998.
[4] J.F. Blinn, "Models of Light Reflection for Computer Synthesized Pictures," Computer Graphics, vol. 11, no. 2, 1977, pp. 192198.
[5] E. Boring and A. Pang, “Interactive Deformations from Tensor Fields,” Proc. IEEE Visualization 98, pp. 297304, 1998.
[6] B. Cabral and L.C. Leedom, "Imaging Vector Fields Using Line Integral Convolution," Computer Graphics (SIGGRAPH '93 Proc.), pp. 263272, 1993.
[7] T. Conturo, N. Lori, T. Cull, E. Akbudak, A. Snyder, J. Shimony, R. McKinstry, H. Burton, and M. Raichle, “Tracking Neuronal Fiber Pathways in the Living Human Brain,” Proc. Nat'l Academy of Sciences, vol. 96, pp. 10,42210,427, 1999.
[8] J. Coremans, R. Luypaert, F. Verhelle, T. Stadnik, and M. Osteaux, “A Method for Myelin Fiber Orientation Mapping Using DiffusionWeighted MR Images,” Magnetic Resonance Imaging, pp. 443454, 1994.
[9] T. Delmarcelle, "The Visualization of SecondOrder Tensor Fields," PhD thesis, Stanford Univ., 1994.
[10] T. Delmarcelle and L. Hesselink, “Visualization of Second Order Tensor Fields and Matrix Data,” Proc. IEEE Visualization 92, pp. 316323, 1992.
[11] T. Delmarcelle and L. Hesselink, “A Unified Framework for Flow Visualization,” Computer Visualization: Graphics Techniques for Scientific and Engineering Analysis, R.S. Gallagher, ed., pp. 129170, CRC Press, 1995.
[12] R.R. Dickinson, “A Unified Approach to the Design of Visualization Software for the Analysis of Field Problems,” ThreeDimensional Visualization and Display Technologies (Proc. SPIE), pp. 173180, 1989.
[13] J.D. Foley,A. van Dam,S.K. Feiner,, and J.F. Hughes,Computer Graphics: Principles and Practice,Menlo Park, Calif.: AddisonWesley, 1990.
[14] V. Interrante and C. Grosch, “Strategies for Effectively Visualizing 3D Flow with Volume LIC,” Proc. IEEE Visualization 97, pp. 421424, 1997.
[15] D.K. Jones, S.C.R. Williams, and M.A. Horsfield, “Full Representation of WhiteMatter Fibre Direction in One Map via Diffusion Tensor Analysis,” Proc. Fifth Int'l Soc. Magnetic Resonance in Medicine, p. 1,743, 1997.
[16] G.D. Kerlick, “Moving Iconic Objects in Scientific Visualization,” Proc. IEEE Visualization 90, pp. 124130, 1990.
[17] G.L. Kindlmann and D.M. Weinstein, HueBalls and LitTensors for Direct Volume Rendering of Diffusion Tensor Fields Proc. IEEE Visualization '99, pp. 183190, 1999.
[18] D.H. Laidlaw et al., "Visualizing Diffusion Tensor Images of the Mouse Spinal Cord," Proc. IEEE Visualization 98, ACM Press, New York, 1998, pp. 127134.
[19] N. Makris, A.J. Worth, G. Sorensen, G.M. Papadimitriou, O. Wu, T.G. Reese, V.J. Wedeen, T.L. Davis, J.W. Stakes, V.S. Caviness, E. Kaplan, B.R. Rosen, D.N. Pandya, and D.N. Kennedy, “Morphometry of in vivo Human White Matter Association Pathways with Diffusion Weighted MRI,” Annals of Neurology, vol. 42, no. 6, pp. 951962, 1997.
[20] S. Mori and P.B. Barker, “Diffusion Magnetic Resonance Imaging: Its Principle and Applications,” The Anatomical Record, vol. 257, no. 3, pp. 102109, June 1999.
[21] J.D. Murray, Mathematical Biology, chapters 9, 14, 15. Berlin: SpringerVerlag, 1993.
[22] G.M. Nielson, H. Hagen, and H. Müller, Scientific Visualization, chapter 17. Los Alamitos, Calif.: IEEE CS Press, 1997.
[23] S. Pajevic and C. Pierpaoli, “Color Schemes to Represent the Orientation of Anisotropic Tissues from Diffusion Tensor Data: Application to White Matter Fiber Tract Mapping in the Human Brain,” Magnetic Resonance in Medicine, vol. 42, no. 3, pp. 526540, 1999.
[24] D.R. Peachey, “Solid Texturing of Complex Surfaces,” Proc. SIGGRAPH 85, vol. 19, pp. 279286, 1985.
[25] C. Pierpaoli and P.J. Basser, “Toward a Quantitative Assessment of Diffusion Anisotropy,” Magnetic Resonance in Medicine, pp. 893906, 1996.
[26] C. Pierpaoli, “Oh No! One More Method for Color Mapping of Fiber Tract Direction Using Diffusion MR Imaging Data,” Proc. Fifth Int'l Soc. Magnetic Resonance in Medicine, p. 1,741, 1997.
[27] H.W. Shen, C. Johnson, and K.L. Ma, “Visualizing Vector Fields Using Line Integral Convolution and Dye Advection,” Proc. IEEE 1996 Symp. Volume Visualization, pp. 6370, 1996.
[28] D. Silver, N. Zabusky, V. Fernandez, and M. Gao, “Ellipsoidal Quantification of Evolving Phenomena,” Scientific Visualization of Natural Phenomena, pp. 573588, 1991.
[29] G. Strang, Linear Algebra and Its Applications, chapter 5.5. Orlando, Fla.: Academic Press, 1976.
[30] A.M. Turing, “The Chemical Basis of Morphogenesis,” Philosophical Trans. Royal Soc. London, vol. 237, no. B, pp. 3772, 1952.
[31] G. Turk, “Generating Textures for Arbitrary Surfaces Using ReactionDiffusion,” Computer Graphics (SIGGRAPH '91 Proc.), T.W. Sederberg, ed., vol. 25, no. 4, pp. 289298, July 1991.
[32] G. Turk and D. Banks, “ImageGuided Streamline Placement,” Computer Graphics (Proc. SIGGRAPH '93), 1996.
[33] A.M. Ulug and P.C.M. van Zijl, “OrientationIndependent Diffusion Imaging without Tensor Diagonalization: Anisotropy Definitions Based on Physical Attributes of the Diffusion Ellipsoid,” J. Magnetic Resonance Imaging, vol. 9, no. 6, pp. 804813, June 1999.
[34] C. Upson, R. Wolff, R. Weinberg, and D. Kerlich, “Two and Three Dimensional Visualization Workshop,” Course No. 19, SIGGRAPH 89, 1989.
[35] S.P. Uselton, “Volume Rendering for Computational Fluid Dynamics: Initial Results,” Technical Report RNR91026, NASNASA Ames Research Center, Sept. 1991.
[36] J.J. van Wijk, “Spot NoiseTexture Synthesis for Data Visualization,” Computer Graphics (SIGGRAPH '91 Proc.), T.W. Sederberg, ed., vol. 25, pp. 309318, July 1991.
[37] C.F. Westin, S. Peled, H. Gubjartsson, R. Kikinis, and F.A. Jolesz, “Geometrical Diffusion Measures for MRI from Tensor Basis Analysis,” Proc. Fifth Ann. Int'l Soc. Magnetic Resonance in Medicine, 1997.
[38] A. Witkin and M. Kass, “ReactionDiffusion Textures,” Computer Graphics (SIGGRAPH '91 Proc.), T.W. Sederberg, ed., vol. 25, no. 4, pp. 299308, July 1991.
[39] A.J. Worth, N. Makris, V.J. Wedeen Jr., V.S. Caviness, and D.N. Kennedy, “Fusion of MRI Data for Visualization of White Matter Bundles,” 1998. ftp://ftp.cs.unc.edu/pub/users/manocha/PAPERS/ VISIBILITY/hom.{ps.gz,pdf}http:// neurowww.mgh.harvard.edu/cma/staff/ajw/ MICCAI98MICCAI98.html.
[40] M. Zöckler, D. Stalling, and H.C. Hege, “Interactive Visualization of 3DVector Fields Using Illuminated Streamlines,” Proc. IEEE Visualization '96, pp. 107113, 1996.