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Issue No.12 - Dec. (2012 vol.18)
pp: 2178-2187
R. Gasteiger , Dept. of Simulation & Graphics, Univ. of Magdeburg, Magdeburg, Germany
D. J. Lehmann , Dept. of Simulation & Graphics, Univ. of Magdeburg, Magdeburg, Germany
R. van Pelt , Dept. of Biomed. Eng., Eindhoven Univ. of Technol., Eindhoven, Netherlands
G. Janiga , Inst. of Fluid Dynamics & Thermodynamics, Univ. of Magdeburg, Magdeburg, Germany
O. Beuing , Dept. of Neuroradiology, Univ. Hosp. Magdeburg, Magdeburg, Germany
A. Vilanova , Dept. of Biomed. Eng., Eindhoven Univ. of Technol., Eindhoven, Netherlands
H. Theisel , Dept. of Simulation & Graphics, Univ. of Magdeburg, Magdeburg, Germany
B. Preim , Dept. of Simulation & Graphics, Univ. of Magdeburg, Magdeburg, Germany
Cerebral aneurysms are a pathological vessel dilatation that bear a high risk of rupture. For the understanding and evaluation of the risk of rupture, the analysis of hemodynamic information plays an important role. Besides quantitative hemodynamic information, also qualitative flow characteristics, e.g., the inflow jet and impingement zone are correlated with the risk of rupture. However, the assessment of these two characteristics is currently based on an interactive visual investigation of the flow field, obtained by computational fluid dynamics (CFD) or blood flow measurements. We present an automatic and robust detection as well as an expressive visualization of these characteristics. The detection can be used to support a comparison, e.g., of simulation results reflecting different treatment options. Our approach utilizes local streamline properties to formalize the inflow jet and impingement zone. We extract a characteristic seeding curve on the ostium, on which an inflow jet boundary contour is constructed. Based on this boundary contour we identify the impingement zone. Furthermore, we present several visualization techniques to depict both characteristics expressively. Thereby, we consider accuracy and robustness of the extracted characteristics, minimal visual clutter and occlusions. An evaluation with six domain experts confirms that our approach detects both hemodynamic characteristics reasonably.
object detection, computational fluid dynamics, data visualisation, haemodynamics, medical image processing, occlusions, automatic detection, automatic visualization, qualitative hemodynamic characteristics, cerebral aneurysms, pathological vessel dilatation, risk of rupture, quantitative hemodynamic information, qualitative flow characteristics, computational fluid dynamics, CFD, blood flow measurements, inflow jet boundary contour, impingement zone, minimal visual clutter, Aneurysm, Data visualization, Hemodynamics, Surface morphology, Rendering (computer graphics), visualization, Cerebral aneurysm, CFD, hemodynamic
R. Gasteiger, D. J. Lehmann, R. van Pelt, G. Janiga, O. Beuing, A. Vilanova, H. Theisel, B. Preim, "Automatic Detection and Visualization of Qualitative Hemodynamic Characteristics in Cerebral Aneurysms", IEEE Transactions on Visualization & Computer Graphics, vol.18, no. 12, pp. 2178-2187, Dec. 2012, doi:10.1109/TVCG.2012.202
[1] S. Appanaboyina, F. Mut, R. Löhner., C. Putman, and J. Cebral, Computational Fluid Dynamics of Stented Intracranial Aneurysms Using Adaptive Embedded Unstructured Grids Numerical Methods in Fluids, 57(5): 475-493, 2008. 1
[2] M. I. Baharoglu,C. M. Schirmer,D. A. Hoit, B.-L. Gao, and A. M., Malek. Aneurysm Inflow-Angle as a Discriminant for Rupture in Side-wall Cerebral Aneurysms Morphometric and Computational Fluid Dynamic Analysis Stroke, 41(7): 1423-1430, 2010. 2
[3] S. Born, M. Pfeifle, M. Markl,, and G. Scheuermann., Visual 4D MRI Blood Flow Analysis With Line Predicates. In Proc. IEEE Pacific Visualization, pages 105-112, 2012. 2
[4] J. R. Cebral,M. A. Castro, S. Appanaboyina, C. M. Putmann,D. Millan,, and A. F. Frangi., Efficient Pipeline for Image-Based Patient-Specific Analysis of Cebral Aneurysm Hemodynamics: Technique and Sensitivity IEEE Transaction on Medical Imaging, 24(4): 457-467, 2005. 3
[5] J. R. Cebral, F. Mut, J. Weir,, and C. M., Putman. Association of Hemodynamic Characteristics and Cerebral Aneurysm Rupture American Journal of Neuroradiology, 32(2): 264-270, 2011. 1, 3, 6, 7
[6] J. R. Cebral, F. Mut, J. Weir,, and C. M., Putman. Quantitative Characterization of the Hemodynamic Environment in Ruptured and Unruptured Brain Aneurysms American Journal of Neuroradiology, 32(1): 145-151, 2011. 1, 2, 3, 7
[7] J. R. Cebral, R. Pergolizzi, and C. M. Putman., Computational Fluid Dynamics Modeling of Intracranial Aneurysms: Qualitative Comparison with Cerebral Angiography Academic Radiology, 14(7): 804-813, 2007. 3
[8] J. R. Cebral, M. Sheridan, and C. M., Putman. Hemodynamics and Bleb Formation in Intracranial Aneurysms. American Journal of Neuroradiology, 31(2): 304-310, 2010. 2
[9] I. Chatziprodromou,V. D. Butty,V. B. Makhijani, D. Poulikakos, and Y. Ventikos, Pulsatile Blood Flow in Anatomically Accurate Vessels with Multiple Aneurysms: A Medical Intervention Planning Application of Computational Hemodynamics Flow, turbulence and combustion, 71(1): 333-346, 2003. 2
[10] M. H. Everts, H. Bekker, J. B. Roerdink,, and T. Isenberg., Depth-Dependent Halos: Illustrative Rendering of Dense Line Data IEEE TVCG, 15(6): 1299-1306, 2009. 5
[11] B. Freudenberg, M. Masuch, and T. Strothotte., Real-Time Halftoning: A Primitive For Non-Photorealistic Shading. In Proc. Eurographics workshop on Rendering, pages 227-232. Eurographics Association, 2002. 5
[12] H. Garcke, T. Preußer, M. Rumpf,A. C. Telea, U. Weikard, and J. J V. Wijk., A Phase Field Model for Continuous Clustering on Vector Fields IEEE TVCG, 7(3): 230-241, 2001. 2
[13] R. Gasteiger, M. Neugebauer, O. Beuing,, and B. Preim., The FLOWLENS: A Focus-and-Context Visualization Approach for Exploration of Blood Flow in Cerebral Aneurysms. IEEE TVCG, 17(12): 2183-2192, 2011. 2
[14] R. Gasteiger, M. Neugebauer, C. Kubisch,, and B. Preim., Adapted Surface Visualization of Cerebral Aneurysms with Embedded Blood Flow Information. In Proc. VCBM, pages 25-32, 2010. 2,5
[15] E. Heiberg, T. Ebbers, L. Wigström,, and M. Karlsson., Three-Dimensional Flow Characterization Using Vector Pattern Matching. IEEE TVCG, 9(3): 313-319, 2003. 2
[16] A. Hennemuth, O. Friman, C. Schumann., J. Bock, J. Drexl., M. Markl, and H.-O. Peitgen., Fast Interactive Exploration of 4D MRI Flow Data. In Proc. SPIE Medical Imaging, 2011. 2
[17] M. Hummel, C. Garth, B. Hamann., H. Hagen, and K. I. Joy., Iris: Illustrative Rendering for Integral Surfaces IEEE TVCG, 16(6): 1319-1328, 2010. 5
[18] A. Kuhn,D. J. Lehmann, R. Gaststeiger, M. Neugebauer., B. Preim, and H. Theisel., A Clustering-based Visualization Technique to Emphasize Meaningful Regions of Vector Fields. In Vision, Modeling, and Visualization, pages 191-198. Eurographics Assosciation, 2011. 2
[19] R. S. Laramee, G. Chen, M. Jankun-Kelly, E. Zhang, and D. Thompson., Bringing Topology-Based Flow Visualization to the Application Domain. In H.-C. Hege, K. Polthier, and G. Scheuermann, editors, , Topology-Based Methods in Visualization II, Mathematics and Visualization, pages 161-176. Springer, 2009. 2
[20] R. S. Laramee, H. Hauser, L. Zhao,, and F. H., Post. Topology-Based Flow Visualization, The State of the Art. In H. Hauser, H. Hagen, and H. Theisel, editors, , Topology-based Methods in Visualization, Mathematics and Visualization, pages 1-19. Springer, 2007. 2
[21] D. Lesage,E. D. Angelini, I. Bloch, and G. Funka-Lea., A Review of 3D Vessel Lumen Segmentation Techniques: Models, Features and Extraction Schemes. Medical Image Analysis, 13(6): 819-845, December 2009. 3
[22] M. Markl, F. Chan, M. Alley., K. Wedding, M. Draney., C. Elkins, D. Parker., R. Wicker, C. Taylor., R. Herfkens, and N. Pelc, Time-Resolved Three-Dimensional Phase-Contrast MRI Journal of Magnetic Resonance Imaging, 17(4): 499-506, 2003. 2
[23] M. Markl, A. Harloff, T. A. Bley, M. Zaitsev, B. Jung., E. Weigang, M. Langer., J. Hennig, and A. Frydrychowicz, Time-Resolved 3D MR Velocity Mapping at 3T: Improved Navigator-Gated Assessment of Vascular Anatomy and Blood Flow Magnetic Resonance Imaging, 25(4): 824-831, 2007. 1
[24] O. Mattausch, T. Theußl, H. Hauser,, and E. Gröller,Strategies for Interactive Exploration of 3D Flow Using Evenly-Spaced Illuminated Streamlines. In Proc. SCCG, pages 230-241, 2003. 2
[25] H. Meng, Z. Wang, Y. Hoi., L. Gao, E. Metaxa,D. D. Swartz,, and J. Kolega., Complex Hemodynamics at the Apex of an Arterial Bifurcation Induces Vascular Remodeling Resembling Cerebral Aneurysm Initiation. Stroke, 38(6): 1924-1931, 2007. 2
[26] M. Neugebauer, V. Diehl, M. Skalej,, and B. Preim., Geometric Reconstruction of the Ostium of Cerebral Aneurysms. In Vision, Modeling, and Visualization, pages 307-314, 2010. 2, 3
[27] M. Neugebauer, R. Gasteiger, O. Beuing,and et al. Map Displays for the Analysis of Scalar Data on Cerebral Aneurysm Surfaces. CGF (EuroVis), 28 (3): 895-902, 2009. 2
[28] A. Perez-Garcia,V. Ayala-Ramirez,R. E. Sanchez-Yanez,, and J.-G. Avina-Cervantes., Monte Carlo Evaluation of the Hausdorff Distance for Shape Matching. In Proceedings of the 11th Iberoamerican conference on Progress in Pattern Recognition, Image Analysis and Applications, CIARP’06, pages 686-695, Berlin, Heidelberg, 2006. Springer-Verlag. 7
[29] F. H. Post, B. Vrolijk, H. Hauser,R. S. Laramee,, and H. Doleisch., Feature Extraction and Visualization of Flow Fields. In Eurographics, 2002. 1
[30] J. Reininghaus, N. Kotava, D. Guenther., J. Kasten, H. Hagen,, and I. Hotz., A Scale Space Based Persistence Measure for Critical Points in 2D Scalar Fields. IEEE TVCG, 17(12): 2045-2052, 2011. 9
[31] T. Salzbrunn and G. Scheuermann, Streamline Predicates IEEE TVCG, 12(6): 1601-1612, 2006. 2
[32] J. Schöberl,NETGEN: An Advancing Front 2D/3D-Mesh Generator Based on Abstract Rules. Computing and Visualization in Science, 1: 41-52, 1997. 3
[33] D. M. Sforza,C. M. Putman,, and J. R. Cebral., Hemodynamics of Cerebral Aneurysms Annual Review of Fluid Mechanics, 41: 91-107, 2009. 1
[34] R. van Pelt,J. O. Bescós, M. Breeuwer, R. E. Clough,, and M. E. Gröller., Exploration of 4D MRI Blood-Flow Using Stylistic Visualization. IEEE TVCG, 16(6): 1339-1347, 2010. 2
[35] R. van Pelt,J. O. Bescós, M. Breeuwer, R. E. Clough,M. E. Groller,B. ter Haar Romenij,, and A. Vilanova., Interactive Virtual Probing of 4D MRI Blood-Flow. IEEE TVCG, 17(12): 2153-2162, 2011. 2, 5
[36] T. Weinkauf and D. Gnther, Separatrix Persistence: Extraction of Salient Edges on Surfaces Using Topological Methods CGF (Proc. SGP), 28(5): 1519-1528, July 2009. 9
[37] M. J. Wermer,I. C. van der Schaaf, A. Algra, and G. J., Rinkel. Risk of Rupture of Unruptured Intracranial Aneurysms in Relation to Patient and Aneurysm Characteristics: An Updated Meta-Analysis Stroke, 38(4): 1404, 2007. 1
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