The Visual Computer

, Volume 25, Issue 11, pp 1019–1035

High-quality cardiac image dynamic visualization with feature enhancement and virtual surgical tool inclusion

Original Article

Abstract

Traditional approaches for rendering segmented volumetric data sets usually deliver unsatisfactory results, such as insufficient frame rate, low image quality, and intermixing artifacts. In this paper, we introduce a novel “color encoding” technique, based on graphics processing unit (GPU) accelerated raycasting and post-color attenuated classification, to address this problem. The result is an algorithm that can generate artifact-free dynamic volumetric images in real time. Next, we present a pre-integrated volume shading algorithm to reduce graphics memory requirements and computational cost when compared to traditional shading methods. We also present a normal-adjustment technique to improve image quality at clipped planes. Furthermore, we propose a new algorithm for color and depth texture indexing that permits virtual solid objects, such as surgical tools, to be manipulated within the dynamically rendered volumetric cardiac images in real time. Finally, all these techniques are combined within an environment that permits real-time visualization, enhancement, and manipulation of dynamic cardiac data sets.

Keywords

Color encoding Cardiac anatomical feature enhancement Boundary color adjustment Volume shading Virtual surgical tools 

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References

  1. 1.
    Boll, D.T., Bossert, A.S., Aschoff, A.J., Hoffmann, M.H., Gilkeson, R.C.: Synergy of MDCT and cine MRI for the evaluation of cardiac motility. Am. J. Roentgenol. 186, S379–S386 (2006) CrossRefGoogle Scholar
  2. 2.
    Bühler, K., Neubauer, A., Hadwiger, M., Wolsfberger, S., Wegenkittl, R.: Interactive 3D techniques for computer aided diagnosis and surgery simulation tools. In: Hruby, W. (ed.) Digital Revolution in Radiology—Bridging the Future of Health Care, 2nd edn. Springer, Berlin (2005) Google Scholar
  3. 3.
    Bullitt, E., Aylward, S.: Volume rendering of segmented image objects. IEEE Trans. Med. Imag. 21(8), 998–1002 (2002). citeseer.ist.psu.edu/bullitt02volume.html CrossRefGoogle Scholar
  4. 4.
    Cabral, B., Cam, N., Foran, J.: Accelerated volume rendering and tomographic reconstruction using texture mapping hardware. In: Proceedings of the 1994 Symposium on Volume Visualization, pp. 91–98. ACM, New York (1994) CrossRefGoogle Scholar
  5. 5.
    Dong, F., Clapworthy, G.: Volumetric texture synthesis for non-photorealistic volume rendering of medical data. Vis. Comput. 21(7), 463–473 (2005) CrossRefGoogle Scholar
  6. 6.
    Engel, K., Kraus, M., Ertl, T.: High-quality pre-integrated volume rendering using hardware-accelerated pixel shading. In: HWWS’01: Proceedings of the ACM SIGGRAPH/EUROGRAPHICS Workshop on Graphics Hardware, pp. 9–16. ACM, New York (2001) CrossRefGoogle Scholar
  7. 7.
    Gelder, A.V., Kim, K.: Direct volume rendering with shading via three-dimensional textures. In: VVS’96: Proceedings of the 1996 Symposium on Volume Visualization, pp. 23–30. IEEE Press, New York (1996) CrossRefGoogle Scholar
  8. 8.
    Hadwiger, M., Berger, C., Hauser, H.: High-quality two-level volume rendering of segmented data sets on consumer graphics hardware. In: VIS’03: Proceedings of the 14th IEEE Visualization 2003 (VIS’03), p. 40. IEEE Computer Society, Los Alamitos (2003). doi:10.1109/VISUAL.2003.1250386 Google Scholar
  9. 9.
    Hadwiger, M., Kniss, J.M., Rezk-Salama, C., Weiskopf, D.: Real-time Volume Graphics. AK Peters, Wellesley (2006) Google Scholar
  10. 10.
    Hauser, H., Mroz, L., Bischi, G.I., Gröller, E.: Two-level volume rendering. IEEE Trans. Vis. Comput. Graph. 7(3), 242–252 (2001) CrossRefGoogle Scholar
  11. 11.
    Higuera, F.V., Hastreiter, P., Naraghi, R., Fahlbusch, R., Greiner, G.: Smooth volume rendering of labeled medical data on consumer graphics hardware. In: Robert, J., Galloway, L., Cleary, K.R. (eds.) Proc. of SPIE Medical Imaging, vol. 5744, pp. 13–21. SPIE, San Diego (2005) Google Scholar
  12. 12.
    Höhne, K., Hanson, W.: Interactive 3D-segmentation of MRI and CT volumes using morphological operations. J. Comput. Assist. Tomogr. 16(2), 285–294 (1992) CrossRefGoogle Scholar
  13. 13.
    Höhne, K.H., Bomans, M., Pommert, A., Riemer, M., Schiers, C., Tiede, U., Wiebecke, G.: 3D visualization of tomographic volume data using the generalized voxel model. Vis. Comput. 6(1), 28–36 (1990). doi:10.1007/BF01902627 CrossRefGoogle Scholar
  14. 14.
    Kniss, J., Kindlmann, G.L., Hansen, C.D.: Multidimensional transfer functions for interactive volume rendering. IEEE Trans. Vis. Comput. Graph. 8(3), 270–285 (2002) CrossRefGoogle Scholar
  15. 15.
    Kniss, J., Premoze, S., Hansen, C.D., Shirley, P., McPherson, A.: A model for volume lighting and modeling. IEEE Trans. Vis. Comput. Graph. 9(2), 150–162 (2003) CrossRefGoogle Scholar
  16. 16.
    Kratz, A., Hadwiger, M., Splechtna, R., Fuhrmann, A., Bühler, K.: GPU-based high-quality volume rendering for virtual environments. In: International Workshop on Augmented Environments for Medical Imaging and Computer Aided Surgery (AMI-ARCS) (2006) Google Scholar
  17. 17.
    Krüger, J., Westermann, R.: Acceleration techniques for GPU-based volume rendering. In: VIS’03: Proceedings of the 14th IEEE Visualization 2003 (VIS’03), pp. 287–292. IEEE Computer Society, Los Alamitos (2003). doi:10.1109/VIS.2003.10001 Google Scholar
  18. 18.
    Lai, H.Y., : CT of two hearts beating in one chest. Am. J. Roentgenol. 191, 1711–1716 (2008) CrossRefGoogle Scholar
  19. 19.
    Lawler, L.P., Ney, D., Pannu, H.K., Fishman, E.K.: Four-dimensional imaging of the heart based on near-isotropic MDCT data sets. Am. J. Roentgenol. 184, 774–776 (2005) Google Scholar
  20. 20.
    Lefebvre, S., Hornus, S., Neyret, F.: Octree textures on the GPU. In: GPU Gems 2–Programming Techniques for High-Performance Graphics and General-Purpose Computation, pp. 595–613. Addison Wesley, Reading (2005). http://www-evasion.imag.fr/Publications/2005/LHN05a Google Scholar
  21. 21.
    Lehmann, H., Ecabert, O., Geller, D., Kiefer, G., Weese, J.: Visualizing the beating heart: interactive direct volume rendering of high-resolution ct time series using standard pc hardware. In: Proceedings of SPIE on Medical Imaging, vol. 6141, San Diego, CA (2006) Google Scholar
  22. 22.
    Levin, D., Aladl, U., Germano, G., Slomka, P.: Techniques for efficient real-time, 3D visualization of multi-modality cardiac data using consumer graphics hardware. Comput. Med. Imaging Graph. 29(6), 463–475 (2005) CrossRefGoogle Scholar
  23. 23.
    Levoy, M.: Display of surfaces from volume data. IEEE Comput. Graph. Appl. 8(3), 29–37 (1988) CrossRefGoogle Scholar
  24. 24.
    Linte, C.A., Wiles, A.D., Moore, J., Wedlake, C., Guiraudon, G., Jones, D., Bainbridge, D., Peters, T.M.: An augmented reality environment for image-guidance of off-pump mitral valve implantation. In: Proc. of SPIE Med. Imaging, vol. 6509, p. 65090N, San Diego, CA (2007) Google Scholar
  25. 25.
    Linte, C.A., Moore, J., Wiles, A.D., Wedlake, C., Peters, T.M.: Virtual reality-enhanced ultrasound guidance: a novel technique for intracardiac interventions. Comput. Aided Surg. 13(2), 82–94 (2008) CrossRefGoogle Scholar
  26. 26.
    Lum, E.B., Wilson, B., Ma, K.-L.: High-Quality Lighting and Efficient Pre-Integration for Volume Rendering. Joint EUROGRAPHICS–IEEE TVCG Symposium on Visualization (2004) Google Scholar
  27. 27.
    Max, N.L.: Optical models for direct volume rendering. IEEE Trans. Vis. Comput. Graph. 1(2), 99–108 (1995) CrossRefGoogle Scholar
  28. 28.
    Mochizuki, N., Makino, M.: A real-time volume rendering of left ventricular activity in human heart. In: 7th International Conference on System Simulation and Scientific Computing (ICSC 2008), pp. 555–561 (2008) Google Scholar
  29. 29.
    Peters, T.M.: Topical review: images for guidance for surgical procedures. Phys. Med. Biol. 51(14), R505–R540 (2006) CrossRefGoogle Scholar
  30. 30.
    Reitinger, B., Schmalstieg, D., Bornik, A., Beichel, R.: Spatial analysis tools for virtual reality-based surgical planning. In: 3DUI’06: Proceedings of the 3D User Interfaces, pp. 37–44. IEEE Computer Society, Los Alamitos (2006) Google Scholar
  31. 31.
    Rezk-Salama, C.: Volume rendering techniques for general purpose graphics hardware. Ph.D. Thesis, University of Siegen, Germany (2001) Google Scholar
  32. 32.
    Rheingans, P., Ebert, D.S.: Volume illustration: nonphotorealistic rendering of volume models. IEEE Trans. Vis. Comput. Graph. 7(3), 253–264 (2001). seer.ist.psu.edu/rheingans01volume.html CrossRefGoogle Scholar
  33. 33.
    Spevak, P.J., Johnson, P.T., Fishman, E.K.: Surgically corrected congenital heart disease: utility of 64-MDCT. Am. J. Roentgenol. 191, 854–861 (2008) CrossRefGoogle Scholar
  34. 34.
    Subramanian, N., Mullick, R., Vaidya, V.: Volume rendering segmented data using 3D textures: a practical approach for intra-operative visualization. In: Cleary, K.R., Robert, J., Galloway, L. (eds.) Proc. of SPIE Medical Imaging, vol. 6141, p. 61412Q. SPIE, San Diego (2006) Google Scholar
  35. 35.
    Termeer, M., Bescós, J.O., Breeuwer, M., Vilanova, A., Gerritsen, F., Gröller, E.: Covicad: Comprehensive visualization of coronary artery disease. IEEE Trans. Vis. Comput. Graph. 13(6), 1632–1639 (2007). http://doi.ieeecomputersociety.org/10.1109/TVCG.2007.70550 CrossRefGoogle Scholar
  36. 36.
    Tiede, U., Schiemann, T., Höhne, K.H.: High quality rendering of attributed volume data. In: Ebert, D., Hagen, H., Rushmeier H. (eds.) IEEE Visualization’98, pp. 255–262 (1998). seer.ist.psu.edu/tiede98high.html
  37. 37.
    van Dam, A., Forsberg, A.S., Laidlaw, D.H., LaViola, J.J., Simpson, R.M.: Immersive VR for scientific visualization: a progress report. IEEE Comput. Graph. Appl. 20(6), 26–52 (2000) CrossRefGoogle Scholar
  38. 38.
    van Ooijen, P.M.A., Ho, K.Y., Dorgelo, J., Oudkerk, M.: Coronary artery imaging with multidetector CT: visualization issues. Radiographics 28, e16 (2003) CrossRefGoogle Scholar
  39. 39.
    Vernhet-Kovacsik, H., : Early postoperative assessment of coronary artery bypass graft patency and anatomy: value of contrast-enhanced 16-MDCT with retrospectively ECG-gated reconstructions. Am. J. Roentgenol. 186, S395–S400 (2006) CrossRefGoogle Scholar
  40. 40.
    Weiskopf, D., Engel, K., Ertl, T.: Interactive clipping techniques for texture-based volume visualization and volume shading. IEEE Trans. Vis. Comput. Graph. 9(3), 298–312 (2003) CrossRefGoogle Scholar
  41. 41.
    Wierzbicki, M., Drangova, M., Guiraudon, G., Peters, T.: Validation of dynamic heart models obtained using non-linear registration for virtual reality training, planning, and guidance of minimally invasive cardiac surgeries. Med. Image Anal. 8(3), 387–401 (2004) CrossRefGoogle Scholar
  42. 42.
    Wu, Y., Qu, H.: Interactive transfer function design based on editing direct volume rendered images. IEEE Trans. Vis. Comput. Graph. 13(5), 1027–1040 (2007) CrossRefGoogle Scholar
  43. 43.
    Zajtchuk, R., Satava, R.M.: Medical applications of virtual reality. Commun. ACM 40(9), 63–64 (1997). http://doi.acm.org/10.1145/260750.260768 CrossRefGoogle Scholar
  44. 44.
    Zhang, Q., Eagleson, R., Peters, T.M.: Real-time visualization of 4D cardiac MR images using graphics processing units. In: ISBI, pp. 343–346. IEEE Press, New York (2006) Google Scholar
  45. 45.
    Zhang, Q., Eagleson, R., Peters, T.M.: GPU-based image manipulation and enhancement techniques for dynamic volumetric medical image visualization. In: ISBI, pp. 1168–1171. IEEE Press, New York (2007) Google Scholar
  46. 46.
    Zhang, Q., Eagleson, R., Peters, T.M.: Rapid voxel classification methodology for interactive 3D medical image visualization. In: Ayache, N., Ourselin, S., Maeder, A.J. (eds.) MICCAI (2). Lecture Notes in Computer Science, vol. 4792, pp. 86–93. Springer, Berlin (2007) Google Scholar
  47. 47.
    Zhang, Q., Huang, X., Eagleson, R., Guiraudon, G., Peters, T.M.: Real-time dynamic display of registered 4D cardiac MR and ultrasound images using a GPU. In: Proceedings of SPIE on Medical Imaging, vol. 6509, pp. 65,092D-1–11. San Diego, CA (2007) Google Scholar
  48. 48.
    Zhang, Q., Eagleson, R., Guiraudon, G.M., Peters, T.M.: High-quality anatomical structure enhancement for cardiac image dynamic volume rendering. In: Miga, M.I., Cleary, K.R. (eds.) Proc. of SPIE Medical Imaging, vol. 6918, p. 691834. SPIE, San Diego (2008) Google Scholar

Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  1. 1.Imaging Research Laboratories, Robarts Research InstituteUniversity of Western OntarioLondonCanada

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