The Community for Technology Leaders
RSS Icon
Issue No.10 - October (2011 vol.17)
pp: 1407-1419
Vesna Prčkovska , Technische Universiteit Eindhoven, Eindhoven
Tim H.J.M. Peeters , Technische Universiteit Eindhoven, Eindhoven
Markus van Almsick , Technische Universiteit Eindhoven, Eindhoven
Bart ter Haar Romeny , Technische Universiteit Eindhoven, Eindhoven
Anna Vilanova , Technische Universiteit Eindhoven, Eindhoven
High-angular resolution diffusion imaging (HARDI) is a diffusion weighted MRI technique that overcomes some of the decisive limitations of its predecessor, diffusion tensor imaging (DTI), in the areas of composite nerve fiber structure. Despite its advantages, HARDI raises several issues: complex modeling of the data, nonintuitive and computationally demanding visualization, inability to interactively explore and transform the data, etc. To overcome these drawbacks, we present a novel, multifield visualization framework that adopts the benefits of both DTI and HARDI. By applying a classification scheme based on HARDI anisotropy measures, the most suitable model per imaging voxel is automatically chosen. This classification allows simplification of the data in areas with single fiber bundle coherence. To accomplish fast and interactive visualization for both HARDI and DTI modalities, we exploit the capabilities of modern GPUs for glyph rendering and adopt DTI fiber tracking in suitable regions. The resulting framework, allows user-friendly data exploration of fused HARDI and DTI data. Many incorporated features such as sharpening, normalization, maxima enhancement and different types of color coding of the HARDI glyphs, simplify the data and enhance its features. We provide a qualitative user evaluation that shows the potentials of our visualization tools in several HARDI applications.
DTI, HARDI, diffusion, GPU, glyphs, multifield.
Vesna Prčkovska, Tim H.J.M. Peeters, Markus van Almsick, Bart ter Haar Romeny, Anna Vilanova, "Fused DTI/HARDI Visualization", IEEE Transactions on Visualization & Computer Graphics, vol.17, no. 10, pp. 1407-1419, October 2011, doi:10.1109/TVCG.2010.244
[1] 3D Slicer, http:/, 2010.
[2] A.L. Alexander, K.M. Hasan, M. Lazar, J.S. Tsuruda, and D.L. Parker, “Analysis of Partial Volume Effects in Diffusion— Tensor MRI,” Magnetic Resonance in Medicine, vol. 45, pp. 770-780, 2001.
[3] D.C. Alexander, G.J. Barker, and S.R. Arridge, “Detection and Modeling of Non-Gaussian Apparent Diffusion Coefficient Profiles in Human Brain Data,” Magnetic Resonance in Medicine, vol. 48, no. 2, pp. 331-340, 2002.
[4] A.W. Anderson, “Measurement of Fiber Orientation Distributions Using High Angular Resolution Diffusion Imaging,” Magnetic Resonance in Medicine, vol. 54, no. 5, pp. 1194-1206, 2005.
[5] P.J. Basser, J. Mattiello, and D. Lebihan, “MR Diffusion Tensor Spectroscopy and Imaging,” Biophysical J., vol. 66, no. 1, pp. 259-267, Jan. 1994.
[6] E. Brunenberg, V. Prčkovska, B. Platel, G. Strijkers, and B. ter Haar Romeny, “Untangling a Fiber Bundle Knot: Preliminary Results on STN Connectivity Using DTI and HARDI on Rat Brains,” Proc. First Ann. Meeting of the Benelux Int'l Soc. of Magnetic Resonance in Medicine, p. 45, 2008.
[7] W. Chen, S. Zhang, S. Correia, and D.F. Tate, “Visualizing Diffusion Tensor Imaging Data with Merging Ellipsoids,” Proc. IEEE Pacific Visualization Symp., pp. 145-151, 2009.
[8] P. Cook, Y. Bai, S. Nedjati-Gilani, K. Seunarine, M. Hall, G. Parker, and D. Alexander, “Camino: Open-Source Diffusion-MRI Reconstruction and Processing,” Proc. 14th Scientific Meeting of the Int'l Soc. for Magnetic Resonance in Medicine, p. 2759, 2006.
[9] R. Deriche and M. Descoteaux, “Splitting Tracking through Crossing Fibers: Multidirectional Q-Ball Tracking,” Proc. Int'l Symp. Biomedical Imaging (ISBI '07), pp. 756-759, 2007.
[10] M. Descoteaux, E. Angelino, S. Fitzgibbons, and R. Deriche, “Apparent Diffusion Coefficients from High Angular Resolution Diffusion Imaging: Estimation and Applications,” Magnetic Resonance in Medicine, vol. 56, no. 2, pp. 395-410, 2006.
[11] M. Descoteaux, E. Angelino, S. Fitzgibbons, and R. Deriche, “Regularized, Fast and Robust Analytical Q-Ball Imaging,” Magnetic Resonance in Medicine, vol. 58, pp. 497-510, 2007.
[12] M. Descoteaux and R. Deriche, “Sharpening Improves Clinically Feasible Q-Ball Imaging Reconstructions,” Proc. Int'l Soc. of Magnetic Resonance in Medicine, p. 906, 2007.
[13] P. Fillard, J. Souplet, and N. Toussaint, Medinria, http:// softwaremedinria, 2010.
[14] L.R. Frank, “Characterization of Anisotropy in High Angular Resolution Diffusion-Weighted MRI,” Magnetic Resonance in Medicine, vol. 47, no. 6, pp. 1083-1099, 2002.
[15] R. Goebel, “Brainvoyager QX,” http:/ Last visited on 2010.
[16] S. Gumhold, “Splatting Illuminated Ellipsoids with Depth Correction,” , Proc. Vision, Modeling, and Visualization, pp. 245-252, 2003.
[17] C. Hess, P. Mukherjee, E. Han, D. Xu, and D. Vigneron, “Q-Ball Reconstruction of Multimodal Fiber Orientations Using the Spherical Harmonic Basis,” Magnetic Resonance in Medicine, vol. 56, pp. 104-117, 2006.
[18] M. Hlawitschka, G. Scheuermann, A. Anwander, T. Knösche, M. Tittgemeyer, and B. Hamann, “Tensor Lines in Tensor Fields of Arbitrary Order,” Proc. Int'l Conf. Advances in Visual Computing (ISVC '07), pp. 341-350, 2007.
[19] S. Jbabdi, M.W. Woolrich, J.L.R. Andersson, and T.E.J. Behrens, “A Bayesian Framework for Global Tractography,” NeuroImage, vol. 37, no. 1, pp. 116-129, Aug. 2007.
[20] Y. Kanamori, Z. Szego, and T. Nishita, “GPU-Based Fast Ray Casting for a Large Number of Metaballs,” Proc. Eurographics '08, vol. 27, no. 3, pp. 351-360, 2008.
[21] G. Kindlmann, “Superquadric Tensor Glyphs,” Proc. Eurographics '04, pp. 147-154, 2004.
[22] S. Mori and P.C. van Zijl, “Fiber Tracking: Principles and Strategies—A Technical Review,” NMR in Biomedicine, vol. 15, nos. 7/8, pp. 468-80, 2002.
[23] E. Özarslan and T.H. Mareci, “Generalized Diffusion Tensor Imaging and Analytical Relationships between Diffusion Tensor Imaging and High Angular Resolution Diffusion Imaging,” Magnetic Resonance in Medicine, vol. 50, no. 5, pp. 955-965, 2003.
[24] E. Özarslan, T.M. Shepherd, B.C. Vemuri, S.J. Blackband, and T.H. Mareci, “Resolution of Complex Tissue Microarchitecture Using the Diffusion Orientation Transform (DOT),” NeuroImage, vol. 36, no. 3, pp. 1086-1103, July 2006.
[25] E. Özarslan, B.C. Vemuri, and T.H. Mareci, “Generalized Scalar Measures for Diffusion MRI Using Trace, Variance, and Entropy,” Magnetic Resonance in Medicine, vol. 53, no. 4, pp. 866-876, 2005.
[26] T.H.J.M. Peeters, V. Prčkovska, M. van Almsick, A. Vilanova, and B.M. ter Haar Romeny, “Fast and Sleek Glyph Rendering for Interactive HARDI Data Exploration,” Proc. IEEE Pacific Visualization Symp., pp. 153-160, 2009.
[27] T.H.J.M. Peeters, A. Vilanova, G.J. Strijkers, and B.M. ter Haar Romeny, “Visualization of the Fibrous Structure of the Heart,” Proc. Vision, Modeling and Visualization, pp. 309-316, 2006.
[28] M. Perrin, Y. Cointepas, C. Poupon, B. Rieul, N. Golestani, D. Rivière, A. Constantinesco, D.L. Bihan, and J.-F. Mangin, “Fiber Tracking in Q-Ball Fields Using Regularized Particle Trajectories,” Proc. Int'l Conf. Information Processing in Medical Imaging (IPMI '05), pp. 52-63, 2005.
[29] V. Prčkovska, A. Vilanova, C. Poupon, B.M. Haar Romeny, and M. Descoteaux, “Fast Classification Scheme for HARDI Data Simplification,” Proc. ICT Innovations '09, pp. 345-355, Springer, 2010.
[30] W. Pullens, A. Roebroeck, and R. Goebel, “Kissing or Crossing: Validation of Fiber Tracking Using Ground Truth Hardware Phantoms,” Proc. Int'l Soc. of Magnetic Resonance in Medicine, p. 1479, 2007.
[31] T. Schultz and H.-P. Seidel, “Estimating Crossing Fibers: A Tensor Decomposition Approach,” IEEE Trans. Visualization and Computer Graphics, vol. 14, no. 6, pp. 1635-1642, Nov./Dec. 2008.
[32] D.W. Shattuck, M.-C. Chiang, M. Barysheva, K.L. McMahon, G.I. de Zubicaray, M. Meredith, M.J. Wright, A.W. Toga, and P.M. Thompson, “Visualization Tools for High Angular Resolution Diffusion Imaging,” Proc. Int'l Conf. Medical Image Computing and Computer-Assisted Intervention (MICCAI '08), pp. 298-305, 2008.
[33] C. Sigg, T. Weyrich, M. Botsch, and M. Gross, “GPU-Based Ray-Casting of Quadratic Surfaces,” Proc. Eurographics '06, pp. 59-65, 2006.
[34] J.D. Tournier, F. Calamante, and A. Connelly, “Robust Determination of the Fibre Orientation Distribution in Diffusion MRI: Non-Negativity Constrained Super-Resolved Spherical Deconvolution,” Neuroimage, vol. 35, no. 4, pp. 1459-1472, 2007.
[35] D. Tuch, “Diffusion MRI of Complex Tissue Structure,” PhD thesis, Harvard Univ., 2002.
[36] D. Tuch, “Q-Ball Imaging,” Magnetic Resonance in Medicine, vol. 52, pp. 1358-1372, 2004.
[37] A. Vilanova, G. Berenschot, and C. van Pul, “DTI Visualization with Stream Surfaces and Evenly-Spaced Volume Seeding,” Proc. IEEE Eurographics '04, pp. 173-182, 2004.
[38] A. Vilanova, S. Zhang, G. Kindlmann, and D. Laidlaw, “An Introduction to Visualization of Diffusion Tensor Imaging and Its Applications,” Visualization and Processing of Tensor Fields, J. Weickert and H. Hagen, eds., pp. 121-153, Springer, 2005.
[39] D. Wassermann, M. Descoteaux, R. Deriche, and C. Westin, “QBall Plug-In for Slicer3D,” software qballslicer, 2010.
85 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool