Abstract
Model generation in VR-based applications is a necessary step in providing a simulated environment to the user. This process is in general a difficult task. The increase of computational power enabled the display of larger virtual environments, thus, reinforcing the need for improved methods for model acquisition, enhancement, optimization, and adaptation. The objects in a VR scene can usually be categorized into either man-made or natural entities. Two general strategies are followed to create these objects—artificial generation or real-world based acquisition. The former technique focuses on manual or semi-automatic design of virtual environments using computer-based modeling tools. In addition, some simple, exactly defined structures can be generated completely automatically following pre-defined procedural formalisms.
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References
Bloch, F.: Nuclear induction. Phys. Rev. 70(7–8), 460–474 (1946)
Boesiger, P.: Kernspin-Tomographie Für die Medizinische Diagnostik. Teubner, Leipzig (1985)
Brooks, F.P.: What’s real about virtual reality? IEEE Comput. Graph. Appl. 19(6), 16–27 (1999)
Brown, J.D., Rosen, J., Kim, Y.S., Chang, L., Sinanan, M., Hannaford, B.: In-vivo and in-situ compressive properties of porcine abdominal soft tissues. In: Westwood, J.D., et al. (eds.) Medicine Meets Virtual Reality, vol. 11, pp. 26–32 (2003)
Bryan, N.R. (ed.): Introduction to the Science of Medical Imaging. Cambridge University Press, Cambridge (2009)
Carter, F.J., Frank, T.G., Davies, P.J., McLean, D., Cuschieri, A.: Measurement and modelling of the compliance of human and porcine organs. Med. Image Anal. 5(4), 231–236 (2001)
Catmull, E.E.: A subdivision algorithm for computer display of curved surfaces. PhD thesis, Department of Computer Science, Univ. of Utah (1974)
Caunce, A., Taylor, C.J.: 3D point distribution models of the cortical sulci. In: Proceeding of Sixth International Conference on Computer Vision, pp. 402–407 (1998)
Chan, S.L., Purisima, E.O.: A new tetrahedral tesselation scheme for isosurface generation. Comput. Graph. 22(1), 83–90 (1998)
Cignoni, P., Montani, C., Scopigno, R.: A comparison of mesh simplification algorithms. Comput. Graph. 22, 37–54 (1997)
Clark, J.H.: Hierarchical geometric models for visible surface algorithms. Commun. ACM 19(10), 547–554 (1976)
Cootes, T.F., Taylor, C.J.: Active shape models—smart snakes. In: Proc. British Machine Vision Conf., pp. 266–275 (1992)
Cormack, A.M.: Representation of a function by its line integrals, with some radiological applications. I. J. Appl. Phys. 34(9), 2722–2727 (1963)
Cormack, A.M.: Representation of a function by its line integrals, with some radiological applications. II. J. Appl. Phys. 35(10), 2908–2913 (1964)
Damadian, R.: Tumor detection by nuclear magnetic resonance. Science 171(3976), 1151–1153 (1971)
Davies, P.J., Carter, F.J., Cuschieri, A.: Mathematical modelling for keyhole surgery simulations: a biomechanical model for spleen tissue. J. Appl. Math. 67(1), 41–67 (2002)
Efros, A.A., Freeman, W.T.: Image quilting for texture synthesis and transfer. In: Proceedings of the 28th Annual Conference on Computer Graphics and Interactive Techniques, pp. 341–346 (2001)
Efros, A.A., Leung, T.: Texture synthesis by non-parametric sampling. In: Computer Vision, 1999. The Proceedings of the Seventh IEEE International Conference on, vol. 2, pp. 1033–1038 (1999)
El-Baz, A.S., Acharya, U.R., Laine, A.F., Suri, J.S. (eds.): Multi Modality State-of-the-Art Medical Image Segmentation and Registration Methodologies, vol. 2. Springer, Berlin (2011)
Erikson, C., Manocha, D., Baxter III, W.V.: HLODs for faster display of large static and dynamic environments. In: 2001 ACM Symposium on Interactive 3D Graphics, pp. 111–120 (2001)
Erikson, K.R., Fry, F.J., Jones, J.P.: Ultrasound in medicine-a review. IEEE Trans. Sonics Ultrason. 21(3), 144–170 (1974)
Fang, S., Chen, H.: Hardware accelerated voxelization. Comput. Graph. 24(3), 433–442 (2000)
Farshad, M., Barbezat, M., Flüeler, P., Schmidlin, F., Graber, P., Niederer, P.: Material characterization of the pig kidney in relation with the biomechanical analysis of renal trauma. J. Biomech. 32(4), 417–425 (1999)
Floater, M.S., Hormann, K.: Surface parameterization: a tutorial and survey. In: Floater, M.S., Sabin, M.A. (eds.) In Advances in Multiresolution for Geometric Modelling, pp. 259–284. Springer, Berlin (2004)
Fowlkes, J.B., Emelianov, S.Y., Pipe, J.G., Skovoroda, A.R., Adler, R.S., Carson, P.L., Sarvazyan, A.P.: Magnetic resonance imaging techniques for detection of elasticity variation. Med. Phys. 22(11), 1771–1778 (1995)
Freixenet, J., Munoz, X., Raba, D., Marti, J., Cufi, X.: Yet another survey on image segmentation: region and boundary information integration. In: ECCV, pp. 408–422 (2002)
Fung, Y.C.: Biomechanics: Mechanical Properties of Living Tissues. Springer, Berlin (1993)
Gagalowicz, A., Ma, S.D.: Sequential synthesis of natural textures. Comput. Vis. Graph. Image Process. 30(3), 289–315 (1985)
Gardner, G.Y.: Simulation of natural scenes using textured quadric surfaces. In: Proceedings of the 11th Annual Conference on Computer Graphics and Interactive Techniques, pp. 11–20 (1984)
Gardner, M.: The fantastic combinations of John Conways’s new solitaire game of life. Sci. Am. 223(4), 120–123 (1970)
Garland, M., Heckbert, P.: Surface simplification using quadric error metrics. In: Proceedings of the 24th Annual Conference on Computer Graphics and Interactive Techniques, pp. 206–216 (1997)
Gauss, C.F.: Disquisitiones generales circa superficies curva (1828)
Harders, M.: Surgical Scene Generation for Virtual Reality-based Training in Medicine. Springer, Berlin (2008)
Harders, M., Bachofen, D., Bajka, M., Grassi, M., Heidelberger, B., Sierra, R., Spaelter, U., Steinemann, D., Teschner, M., Tuchschmid, S., Zatonyi, J., Székely, G.: Virtual reality based simulation of hysteroscopic interventions. Presence 17(5), 441–462 (2008)
Heckbert, P.S.: Survey of texture mapping. IEEE Comput. Graph. Appl. 6(11), 56–67 (1986)
Heimann, T., Meinzer, H.-P.: Statistical shape models for 3D medical image segmentation: a review. Med. Image Anal. 13(4), 543–563 (2009)
Hoppe, H., DeRose, T., Duchamp, T., McDonald, J., Stuetzle, W.: Mesh optimization. In: Proceedings of the 20th Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH ’93, pp. 19–26 (1993)
Hounsfield, G.N.: Computerised transverse axial scanning (tomography): Part 1. Description of system. Br. J. Radiol. 46, 1016–1022 (1973)
Hsieh, J.: Computed Tomography: Principles, Design, Artifacts, and Recent Advances, vol. PM114. SPIE Press, Bellingham (2003)
Hug, C., Brechbühler, J., Székely, G.: Model-based initialisation for segmentation. In: Proceedings 6’th European Conference on Computer Vision—ECCV 2000, Part II, pp. 290–306 (2000)
Hug, J.: Semi-automatic segmentation of medical imagery. PhD thesis, ETH Zurich (2001)
Jolliffe, I.T.: Principal Component Analysis. Springer, Berlin (2002)
Kalberer, G.A., Van Gool, L.: Realistic face animation for speech. J. Vis. Comput. Animat. 13(2), 97–106 (2002)
Kansal, A.R., Torquato, S., Harsh, G.R., Chiocca, E.A., Deisboeck, T.S.: Simulated brain tumor growth dynamics using a three-dimensional cellular automaton. J. Theor. Biol. 203(4), 367–382 (2000)
Karabassi, E.-A., Papaioannou, G., Theoharis, T.: A fast depth-buffer-based voxelization algorithm. J. Graph. Tools 4, 5–10 (1999)
Kauer, M.: Inverse finite element characterization of soft tissues with aspiration experiments. PhD thesis, ETH Zurich (2001)
Kauer, M., Vuskovic, V., Dual, J., Szekely, G., Bajka, M.: Inverse finite element characterization of soft tissues. Med. Image Anal. 6(3), 275–287 (2002)
Kelemen, A., Szekely, G., Gerig, G.: Elastic model-based segmentation of 3-D neuroradiological data sets. IEEE Trans. Med. Imaging 18(10), 828–839 (1999)
Kerdok, A.E., Ottensmeyer, M.P., Howe, R.D.: Effects of perfusion on the viscoelastic characteristics of liver. J. Biomech. 39(12), 2221–2231 (2006)
Kim, J., Tay, B.K., Stylopoulos, N., Rattner, D.W., Srinivasan, M.A.: Characterization of intra-abdominal tissues from in vivo animal experiments for surgical simulation. In: Medical Image Computing and Computer-assisted Intervention, pp. 206–213 (2003)
Kobbelt, L., Campagna, S., Vorsatz, J., Seidel, H.-P.: Interactive multi-resolution modeling on arbitrary meshes. In: Proceedings of the 25th Annual Conference on Computer Graphics and Interactive Techniques, pp. 105–114 (1998)
Kotcheff, A.C.W., Taylor, C.J.: Automatic construction of eigenshape models by direct optimization. Med. Image Anal. 2(4), 303–314 (1998)
Lauterbur, P.C.: Image formation by induced local interactions: examples employing nuclear magnetic resonance. Nature 242, 190–191 (1973)
Lindenmayer, A.: Mathematical models for cellular interaction in development: Parts I and II. J. Theor. Biol. 18(3), 300–315 (1968)
Lindstrom, P., Turk, G.: Fast and memory efficient polygonal simplification. In: Proceedings of the Conference on Visualization ’98, VIS ’98, pp. 279–286 (1998)
Lorensen, W.E., Cline, H.E.: Marching cubes: a high resolution 3D surface construction algorithm. In: Proceedings of the 14th Annual Conference on Computer Graphics and Interactive Techniques, vol. 21, pp. 163–169 (1987)
Mansfield, P.: Multi-planar image formation using NMR spin echoes. J. Phys. C, Solid State Phys. 10(3), 55–58 (1977)
Mayles, P., Nahum, A., Rosenwald, J.C.: Handbook of Radiotherapy Physics: Theory and Practice. Taylor and Francis, London (2007)
McInerney, T., Terzopoulos, D.: Deformable models in medical image analysis: a survey. Med. Image Anal. 1(2), 91–108 (1996)
Mueller, P., Wonka, P., Haegler, S., Ulmer, A., Van Gool, L.: Procedural modeling of buildings. ACM SIGGRAPH 2006 Pap. 25(3), 614–623 (2006)
Muthupillai, R., Lomas, D.J., Rossman, P.J., Greenleaf, J.F., Manduca, A., Ehman, R.L.: Magnetic resonance elastography by direct visualization of propagating acoustic strain waves. Science 269(5232), 1854–1857 (1995)
Nadernejad, E., Sharifzadeh, S., Hassanpour, H.: Edge detection techniques: evaluations and comparisons. Appl. Math. Sci. 2(31), 1507–1520 (2008)
Nava, A., Mazza, E., Kleinermann, F., Avis, N.J., McClure, J.: Evaluation of the mechanical properties of human liver and kidney through aspiration experiments. Technol. Health Care 12(3), 269–280 (2004)
Newman, T.S., Yia, H.: A survey of the marching cubes algorithm. Comput. Graph. 30(5), 854–879 (2006)
Nielson, G.M., Hamann, B.: The asymptotic decider: resolving the ambiguity in marching cubes. In: Proceedings of the 2nd Conference on Visualization ’91, pp. 83–91 (1991)
Oliensis, J.: Local reproducible smoothing without shrinkage. IEEE Trans. Pattern Anal. Mach. Intell. 15(3), 307–312 (1993)
Ophir, J., Cespedes, I., Ponnekanti, H., Yazdi, Y., Li, X.: Elastography: a method for imaging the elasticity of biological tissues. Ultrason. Imaging 13(2), 111–134 (1991)
Ottensmeyer, M.P.: In vivo measurement of solid organ visco-elastic properties. In: Medicine Meets Virtual Reality, vol. 85, pp. 328–333 (2002)
Ottensmeyer, M.P., Kerdok, A.E., Howe, R.D., Dawson, S.: The effects of testing environment on the viscoelastic properties of soft tissues. In: Medical Simulation, vol. 3078, pp. 9–18 (2004)
Paget, R., Harders, M., Szekely, G.: A framework for coherent texturing in surgical simulators. In: Proceedings of the 13th Pacific Conference on Computer Graphics and Applications, pp. 112–114 (2005)
Pal, N.R., Pal, S.K.: A review on image segmentation techniques. Pattern Recognit. 26(9), 1277–1294 (1993)
Peachey, D.R.: Solid texturing of complex surfaces. In: Proceedings of the 12th Annual Conference on Computer Graphics and Interactive Techniques, pp. 279–286 (1985)
Perlin, K.: An image synthesizer. In: Proceedings of the 12th Annual Conference on Computer Graphics and Interactive Techniques, pp. 287–296 (1985)
Pham, D.L., Xu, C., Price, J.: A survey of current methods in medical image segmentation. Annu. Rev. Biomed. Eng. 2, 315–338 (2000)
Prusinkiewicz, P., Hanan, J., Mech, R.: An l-system-based plant modeling language. In: Proceedings of the International Workshop on Applications of Graph Transformations with Industrial Relevance, AGTIVE ’99, pp. 395–410 (2000)
Prusinkiewicz, P., Lindenmayer, A.: The Algorithmic Beauty of Plants. Springer, Berlin (1990)
Purcell, E.M., Torrey, H.C., Pound, R.V.: Resonance absorption by nuclear magnetic moments in a solid. Phys. Rev. 69(1–2), 37–38 (1946)
Qi, A.S., Zheng, X., Du, C.Y., An, B.S.: A cellular automaton model of cancerous growth. J. Theor. Biol. 161(1), 1–12 (1993)
Radon, J.: Über die Bestimmung von Funktionen durch ihre Integralwerte längs gewisser Mannigfaltigkeiten. Rep. Proc. Sax. Acad. Sci. 69, 262–277 (1917)
Reddy, M.: SCROOGE: Perceptually-driven polygon reduction. Comput. Graph. 15(4), 191–203 (1996)
Roerdink, J.B.T.M., Meijster, A.: The watershed transform: definitions, algorithms and parallelization strategies. Fundam. Inform. 41, 187–228 (2000)
Röntgen, W.C.: Über Eine Neue Art Von Strahlen. Sitzungsberichte der Würzburger Physik.-medic. Gesellschaft (1895)
Sahoo, P.K., Soltani, S., Wong, A.K.C., Chen, Y.C.: A survey of thresholding techniques. Comput. Vis. Graph. Image Process. 41(2), 233–260 (1988)
Schreiner, W., Buxbaum, P.F.: Computer optimization of vascular trees. IEEE Trans. Biomed. Eng. 40(5), 482–491 (1993)
Schroeder, W.J., Zarge, J.A., Lorensen, W.E.: Decimation of triangle meshes. Comput. Graph. 26, 65–70 (1992)
Sheffer, A., Hart, J.C.: Seamster: inconspicuous low-distortion texture seam layout. In: Proceedings of the Conference on Visualization ’02, pp. 291–298 (2002)
Sheffer, A., Levy, B., Mogilnitsky, M., Bogomyakov, A.: ABF++: fast and robust angle based flattening. ACM Trans. Graph. 24(2), 311–333 (2005)
Sierra, R., Szekely, G., Bajka, M.: Generation of pathologies for surgical training simulators. In: Proceedings of Medical Image Computing and Computer-assisted Intervention, vol. 2, pp. 202–210 (2002)
Sierra, R., Zsemlye, G., Szekely, G., Bajka, M.: Generation of variable anatomical models for surgical training simulators. Med. Image Anal. 10(2), 275–285 (2006)
Sinkus, R., Weiss, S., Wigger, E., Lorenzen, J., Dargatz, M., Kuhl, C.: Non-linear elastic tissue properties of the breast measured by mr-elastography—initial in-vitro and in-vivo results. In: ISMRM 10th Annual Meeting, p. 33 (2002)
Spitzer, V., Ackerman, M.J., Scherzinger, A.L., Whitlock, D.: The visible human male: a technical report. J. Am. Med. Inform. Assoc. 3(2), 118–130 (1996)
Staib, L.H., Duncan, J.S.: Boundary finding with parametrically deformable models. IEEE Trans. Pattern Anal. Mach. Intell. 14(11), 1061–1075 (1992)
Styner, M.A., Rajamani, K.T., Nolte, L.P., Zsemlye, G., Szekely, G., Taylor, C.J., Davies, R.H.: Evaluation of 3D correspondence methods for model building. In: Information Processing in Medical Imaging, vol. 18, pp. 63–75 (2003)
Szczerba, D., Szekely, G.: Macroscopic modelling of vascular systems. In: Medical Image Computing and Computer-Assisted Intervention, pp. 284–292 (2002)
Szekely, G., Bajka, M., Brechbuehler, C., Dual, J., Enzler, R., Haller, U., Hug, J., Hutter, R., Ironmonger, N., Kauer, M., Meier, V., Niederer, P., Rhomberg, A., Schmid, P., Schweitzer, G., Thaler, M., Vuskovic, V., Troester, G.: Virtual reality-based simulation of endoscopic surgery. Presence 9(3), 310–333 (2000)
Taubin, G.: Curve and surface smoothing without shrinkage. In: Fifth International Conference on Computer Vision, pp. 852–857 (1995)
Treece, G.M., Prager, R.W., Gee, A.H.: Regularised marching tetrahedra: Improved iso-surface extraction. Comput. Graph. 23(4), 583–598 (1998)
Tuchschmid, S., Bajka, M., Szczerba, D., Lloyd, B., Szekely, G., Harders, M.: Modelling intravasation of liquid distension media in surgical simulators. In: Medical Image Computing and Computer-Assisted Intervention, vol. 4791, pp. 717–724 (2007)
Van Gool, L., Defoort, F., Hug, J., Kalberer, G.A., Koch, R., Martens, D., Pollefeys, M., Proesmans, M., Vergauen, M., Zalesny, A.: Image-based 3D modeling: modeling from reality. In: Leonardis, A., Solina, F., Bajcsy, R. (eds.) Confluence of Computer Vision and Computer Graphics, vol. 84, pp. 161–178. Kluwer, Dordrecht (2000)
Vemuri, B.C., Radisavljevic, A.: Multiresolution stochastic hybrid shape models with fractal priors. ACM Trans. Graph. 13(2), 177–207 (1994)
von Neumann, J.: Theory of Self-reproducing Automata. University of Illinois Press, Champaign (1966)
Wardetzky, M., Mathur, S., Kälberer, F., Grinspun, E.: Discrete Laplace operators: no free lunch. In: Proceedings of the Fifth Eurographics Symposium on Geometry Processing, vol. 19, pp. 33–37 (2007)
Wasserman, R., Acharya, R.: A patient-specific in vivo tumor model. Math. Biosci. 136(2), 111–140 (1996)
Wei, L.-Y., Levoy, M.: Fast texture synthesis using tree-structured vector quantization. In: Proceedings of the 27th Annual Conference on Computer Graphics and Interactive Techniques, pp. 479–488 (2000)
Weishaupt, D., Koechli, V.D., Marincek, B.: How Does MRI Work? An Introduction to the Physics and Function of Magnetic Resonance Imaging, 2nd edn. Springer, Berlin (2003)
Yamada, H.: Strength of Biological Materials. Williams and Wilkins Company, Baltimore (1970)
Ziou, D., Tabbone, S.: Edge detection techniques—an overview. Int. J. Pattern Recognit. Image Anal. 8, 537–559 (1998)
Zitova, B.: Image registration methods: a survey. Image Vis. Comput. 21(11), 977–1000 (2003)
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Riener, R., Harders, M. (2012). Medical Model Generation. In: Virtual Reality in Medicine. Springer, London. https://doi.org/10.1007/978-1-4471-4011-5_10
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