Abstract
In the context of computer-based simulation, contact management requires an accurate, smooth, but still efficient surface model for the blood vessels. A new implicit model is proposed, consisting of a tree of local implicit surfaces generated by skeletons (blobby models). The surface is reconstructed from data points by minimizing an energy, alternating with an original blob selection and subdivision scheme. The reconstructed models are very efficient for simulation and were shown to provide a sub-voxel approximation of the vessel surface on 5 patients.
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Keywords
- Computational Fluid Dynamics
- Subdivision Scheme
- Implicit Surface
- Vessel Surface
- Energy Minimization Problem
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References
Bernhardt, A., Barthe, L., Cani, M.P., et al.: Implicit blending revisited. Comput. Graph. Forum 29(2), 367–375 (2010)
Dequidt, J., Duriez, C., Cotin, S., Kerrien, E.: Towards Interactive Planning of Coil Embolization in Brain Aneurysms. In: Yang, G.-Z., Hawkes, D., Rueckert, D., Noble, A., Taylor, C. (eds.) MICCAI 2009, Part I. LNCS, vol. 5761, pp. 377–385. Springer, Heidelberg (2009)
Goldman, R.: Curvature formulas for implicit curves and surfaces. Computer Aided Geometric Design 22, 632–658 (2005)
Lesage, D., Angelini, E., Bloch, I., et al.: A review of 3D vessel lumen segmentation techniques: Models, features and extraction schemes. Med. Image Anal. 13(6), 819–845 (2009)
Masutani, Y., Masamune, K., Dohi, T.: Region-growing Based Feature Extraction Algorithm for Tree-like Objects. In: Höhne, K.H., Kikinis, R. (eds.) VBC 1996. LNCS, vol. 1131, pp. 159–171. Springer, Heidelberg (1996)
Muraki, S.: Volumetric shape description of range data using blobby model. SIGGRAPH Comput. Graph. 25, 227–235 (1991)
Preim, B., Oeltze, S.: 3D visualization of vasculature: An overview. In: Visualization in Medicine and Life Sciences. Math. and Vis., pp. 39–59. Springer (2008)
Schumann, C., Neugebauer, M., Bade, R., et al.: Implicit vessel surface reconstruction for visualization and CFD simulation. IJCARS 2(5), 275–286 (2008)
Sherstyuk, A.: Kernel functions in convolution surfaces: A comparative analysis. The Visual Computer 15(4), 171–182 (1999)
Taubin, G.: Estimation of planar curves, surfaces, and nonplanar space curves defined by implicit equations with applications to edge and range image segmentation. IEEE Trans. on PAMI 13, 1115–1138 (1991)
Tsingos, N., Bittar, E., Cani, M.P.: Implicit surfaces for semi-automatic medical organ reconstruction. In: Computer Graphics Internat (CGI 1995), pp. 3–15 (1995)
Tyrrell, J., di Tomaso, E., Fuja, D., et al.: Robust 3-D modeling of vasculature imagery using superellipsoids. IEEE Trans. Med. Imag. 26(2), 223–237 (2007)
Yureidini, A., Kerrien, E., Cotin, S.: Robust RANSAC-based blood vessel segmentation. In: SPIE Medical Imaging, vol. 8314, p. 83141M. SPIE (2012)
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Yureidini, A., Kerrien, E., Dequidt, J., Duriez, C., Cotin, S. (2012). Local Implicit Modeling of Blood Vessels for Interactive Simulation. In: Ayache, N., Delingette, H., Golland, P., Mori, K. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2012. MICCAI 2012. Lecture Notes in Computer Science, vol 7510. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33415-3_68
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DOI: https://doi.org/10.1007/978-3-642-33415-3_68
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