Advertisement

Out-of-Core Rendering of Large Volumetric Data Sets at Multiple Levels of Detail

  • Paulo Henrique Junqueira Amorim
  • Thiago Franco de Moraes
  • Jorge Vicente Lopes da Silva
  • Helio PedriniEmail author
Chapter

Abstract

Advances in equipments and techniques for image acquisition have contributed to the availability of massive high-resolution data volumes. Several fields of knowledge have benefited from these technological improvements, such as medicine, geology, biology, fluid dynamics, remote sensing and surveillance, among others. For instance, computed tomography, ultrasonography and magnetic resonance imaging are commonly employed in non-invasive medical diagnosis. More recently, X-ray microtomography imaging techniques have allowed for higher resolution images. The visualization of such large volume data sets using traditional in-core volume rendering has serious limitations, since all data may not fit in the computer’s primary memory. To address such a problem, this work presents an architecture for out-of-core volume rendering at multiple levels of detail. Experiments conducted on several data volumes demonstrate the effectiveness of the proposed approach in terms of memory storage and computational time required in the rendering process, signal-to-noise ratio measured at each level of detail for the rendered volumes as well as frame rate during the user’s interaction.

Keywords

Out-of-core architecture Volumetric visualization Image compression Volume rendering 

Notes

Acknowledgements

The authors are grateful to São Paulo Research Foundation (grants FAPESP #2011/22749-8 and #2013/07559-3) and National Council for Scientific and Technological Development (grant CNPq #307113/2012-4) for their financial support to this research. They are also thankful to Cristiane Ibanhes Polo, from the Department of Oral and Maxillofacial Surgery and Traumatology, Faculty of Dentistry, University of São Paulo, Brazil, for providing Materials A and B.

References

  1. 1.
    A. Agrawal, J. Kohout, G.J. Clapworthy, N.J. Mcfarlane, F. Dong, M. Viceconti, F. Taddei, D. Testi, Enabling the interactive display of large medical volume datasets by multiresolution bricking. J. Supercomput. 51(1), 3–19 (2010)CrossRefGoogle Scholar
  2. 2.
    P. Amorim, T. Moraes, J. Silva, H. Pedrini, An out-of-core volume rendering architecture, in IV ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing, Funchal (CRC Press, Boca Raton, 2013), pp. 173–179Google Scholar
  3. 3.
    P. Amorim, T. Moraes, J. Silva, H. Pedrini, InVesalius: an interactive rendering framework for health care support, in International Symposium on Visual Computing, Las Vegas (Springer, Berlin, 2015), pp. 45–54Google Scholar
  4. 4.
    J. Baert, A. Lagae, P. Dutré, Out-of-core construction of sparse voxel octrees. Comput. Graphics Forum 33(6), 220–227 (2014)CrossRefGoogle Scholar
  5. 5.
    M. Balsa Rodríguez, E. Gobbetti, J.A. Iglesias Guitián, M. Makhinya, F. Marton, R. Pajarola, S.K. Suter, State-of-the-art in compressed GPU-based direct volume rendering. Comput. Graphics Forum 33(6), 77–100 (2014)CrossRefGoogle Scholar
  6. 6.
    J. Beyer, M. Hadwiger, H. Pfister, State-of-the-art in GPU-based large-scale volume visualization. Comput. Graphics Forum 34(8), 13–37 (2015)CrossRefGoogle Scholar
  7. 7.
    G. Carnielli, A. Falcão, J. Udupa, Fast digital perspective shell rendering, in XII Brazilian Symposium on Computer Graphics and Image Processing, Campinas (1999), pp. 105–111Google Scholar
  8. 8.
    H.H. Chen, T.S. Huang, A survey of construction and manipulation of octrees. Comput. Vis. Graphics Image Process. 43(3), 409–431 (1988)CrossRefGoogle Scholar
  9. 9.
    Y. Cheng, L. Jiang, X. Ma, J. Xue, Z. Zheng, Multi-resolution texture rendering for medical data, in Digital Media and Digital Content Management, Hangzhou (2011), pp. 166–171Google Scholar
  10. 10.
    J.J. Choi, B.-S. Shin, Y.G. Shin, K. Cleary, Efficient volumetric ray casting for isosurface rendering. Comput. Graphics 24(5), 661–670 (2000)CrossRefGoogle Scholar
  11. 11.
    T.H. Cormen, C.E. Leiserson, R.L. Rivest, C. Stein, Introduction to Algorithms (MIT Press, Cambridge, 2009)Google Scholar
  12. 12.
    D. Dhamdhere, Operating Systems (McGraw-Hill Higher Education, New York, 2006)Google Scholar
  13. 13.
    S. Dunne, S. Napel, B. Rutt, Fast reprojection of volume data, in Proceedings of the First Conference on Visualization in Biomedical Computing, Atlanta (IEEE, Los Alamitos, 1990), pp. 11–18Google Scholar
  14. 14.
    D. Ellsworth, L.-J. Chiang, H.-W. Shen, Accelerating time-varying hardware volume rendering using TSP trees and color-based error metrics, in Proceedings of the 2000 IEEE Symposium on Volume Visualization, Salt Lake City (ACM, New York, 2000), pp. 119–128Google Scholar
  15. 15.
    T. Ertl, Computer Graphics: Principles and Practice (Springer, Berlin, 1996)Google Scholar
  16. 16.
    T. Fogal, A. Schiewe, J. Krüger, An analysis of scalable GPU-based Ray-guided volume rendering, in IEEE Symposium on Large-Scale Data Analysis and Visualization, vol. 2013 (2013), p. 43. NIH Public AccessGoogle Scholar
  17. 17.
    N. Fout, K.-L. Ma, Fuzzy volume rendering. IEEE Trans. Vis. Comput. Graph. 18(12), 2335–2344 (2012)CrossRefGoogle Scholar
  18. 18.
    S.F. Frisken, R.N. Perry, Simple and efficient traversal methods for quadtrees and octrees. J. Graphics Tools 7, 2002 (2002)CrossRefGoogle Scholar
  19. 19.
    H. Fuchs, Z. M. Kedem, B.F. Naylor, On visible surface generation by a priori tree structures. SIGGRAPH Comput. Graphics 14(3), 124–133 (1980)CrossRefGoogle Scholar
  20. 20.
    M. Hadwiger, P. Ljung, C.R. Salama, T. Ropinski, Advanced illumination techniques for GPU volume raycasting, in ACM SIGGRAPH Asia Courses (ACM, New York, 2008)Google Scholar
  21. 21.
    M. Hadwiger, J. Beyer, W.-K. Jeong, H. Pfister, Interactive volume exploration of petascale microscopy data streams using a visualization-driven virtual memory approach. IEEE Trans. Vis. Comput. Graph. 18(12), 2285–2294 (2012)CrossRefGoogle Scholar
  22. 22.
    K.H. Höhne, H. Fuchs, S.M. Pizer, 3D Imaging in Medicine: Algorithms, Systems, Applications, vol. 60 (Springer Science & Business Media, New York, 2012)Google Scholar
  23. 23.
    T. Huang, G. Fox, Collaborative annotation of real time streams on android-enabled devices, in International Conference on Collaboration Technologies and Systems, Denver (2012), pp. 39–44Google Scholar
  24. 24.
    E.C. La Mar, B. Hamann, K.I. Joy, Multiresolution techniques for interactive texture-based volume visualization, in Conference on Visualization: Celebrating Ten Years, San Francisco (1999), pp. 355–361Google Scholar
  25. 25.
    P. Lacroute, M. Levoy, Fast volume rendering using a shear-warp factorization of the viewing transformation, in 21st Annual Conference on Computer Graphics and Interactive Techniques, Orlando (ACM, New York, 1994), pp. 451–458Google Scholar
  26. 26.
    M. Levoy, Efficient ray tracing of volume data. ACM Trans. Graphics 9(3), 245–261 (1990)CrossRefGoogle Scholar
  27. 27.
    F. Lundell, Out-of-core multi-resolution volume rendering of large data sets. Master’s thesis, Linköpings Universitet, 2011Google Scholar
  28. 28.
    T. Malzbender, Fourier volume rendering. ACM Trans. Graphics 12(3), 233–250 (1993)CrossRefGoogle Scholar
  29. 29.
  30. 30.
  31. 31.
  32. 32.
  33. 33.
    T.F. Moraes, P.H. Amorim, J.V. da Silva, H. Pedrini, M.I. Meurer, Medical volume rendering based on gradient information, in 5th Eccomas Thematic Conference on Computational Vision and Medical Image Processing, Tenerife (CRC Press, Boca Raton, 2015), pp. 181–186Google Scholar
  34. 34.
    D. Nagayasu, F. Ino, K. Hagihara, A decompression pipeline for accelerating out-of-core volume rendering of time-varying data. Comput. Graphics 32(3), 350–362 (2008)CrossRefGoogle Scholar
  35. 35.
  36. 36.
    F.H. Post, G. Nielson, G.-P. Bonneau, Data Visualization: The State of The Art, vol. 713 (Springer Science & Business Media, New York, 2012)Google Scholar
  37. 37.
    D.F. Rogers, R. Earnshaw, State of the Art in Computer Graphics: Aspects of Visualization, 1st edn. (Springer Publishing Company, Incorporated, New York, 2014)Google Scholar
  38. 38.
    D. Salomon, Data Compression: The Complete Reference, 4th edn. (Springer, London, 2006)Google Scholar
  39. 39.
    H. Samet, Implementing ray tracing with octrees and neighbor finding. Comput. Graphics 13, 445–460 (1989)CrossRefGoogle Scholar
  40. 40.
    H. Samet, The Design and Analysis of Spatial Data Structures, vol. 85 (Addison-Wesley Longman Publishing Co., Inc., Boston, 1990)Google Scholar
  41. 41.
    H. Samet, Foundations of Multidimensional and Metric Data Structures. Data Management Systems (Morgan Kaufmann, Burlington, 2012)Google Scholar
  42. 42.
    M. Scholz, J. Bender, C. Dachsbacher, Real-time isosurface extraction with view-dependent level of detail and applications. Comput. Graphics Forum 34(1), 103–115 (2015)CrossRefGoogle Scholar
  43. 43.
    J.P. Schulze, U. Lang, The parallelized perspective shear-warp algorithm for volume rendering. Parallel Comput. 29(3), 339–354 (2003)CrossRefGoogle Scholar
  44. 44.
    R. Sharma, M. Garg, Comparative analysis of JPEG DCT, Haar & Daubechies wavelet, fractal for image compression. Int. J. Adv. Res. Comput. Sci. Softw. Eng. 4(1), 1227–1234 (2014)Google Scholar
  45. 45.
    M. Shih, Y. Zhang, K.-L. Ma, J. Sitaraman, D. Mavriplis, Out-of-core visualization of time-varying hybrid-grid volume data, in IEEE 4th Symposium on Large Data Analysis and Visualization (2014), pp. 93–100Google Scholar
  46. 46.
    A.C. Telea, Data Visualization: Principles and Practice (CRC Press, Boca Raton, 2014)CrossRefGoogle Scholar
  47. 47.
    J. Udupa, D. Odhner , Shell rendering. IEEE Comput. Appl. 13(6), 58–67 (1993)CrossRefGoogle Scholar
  48. 48.
    A. Van Gelder, K. Kim, Direct volume rendering with shading via three-dimensional textures, in Symposium on Volume Visualization, San Francisco (IEEE, Los Alamitos, 1996), pp. 23–30Google Scholar
  49. 49.
    M. Weiler, T. Klein, T. Ertl, Direct volume rendering in OpenSG. Comput. Graphics 28(1), 93–98 (2004)CrossRefGoogle Scholar
  50. 50.
    L. Westover, Footprint evaluation for volume rendering. ACM SIGGRAPH Comput. Graphics 24(4), 367–376 (1990)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Paulo Henrique Junqueira Amorim
    • 1
  • Thiago Franco de Moraes
    • 1
  • Jorge Vicente Lopes da Silva
    • 1
  • Helio Pedrini
    • 2
    Email author
  1. 1.Division of 3D TechnologiesCenter for Information Technology Renato ArcherCampinasBrazil
  2. 2.Institute of ComputingUniversity of CampinasCampinasBrazil

Personalised recommendations