Immersive Visualization of Cellular Structures

  • Sinan Kockara
  • Nawab Ali
  • Serhan Dagtas
Chapter
Part of the International Series in Operations Research & Management Science book series (ISOR, volume 132)

Abstract

Bioimaging is an immensely powerful tool in biomedical research that aids the understanding of cellular structures and the molecular events in the cell. Understanding the biological functions within the cell requires an in-depth understanding of all the diverse functions of the microscopic structures and the molecular interactions between macromolecules in their natural environment. Traditionally, cell biologists have used light microscopy techniques to study topographical characterization of cell surfaces. The optical properties of a light microscope give occasion to a blurring phenomenon similar to the one with a conventional microscope with the result that images are characterized by low resolution and magnification. We address the challenging task of enhancing the image produced by a light microscope by reconstructing a stack of monoscopic images from a light microscope to produce a single image with inferential and useful information than that obtained at the best focus level. We believe such an approach will enable a wider base of microscope users to take advantage of light microscope imaging in biological research.

Keywords

Entropy Dust Macromolecule Cabral 

References

  1. Borovkov AA (1984) Mathematical Statistics (Mir, Moscow, 1984).Google Scholar
  2. Cabral B, Cam N, Foran J (1994) Accelerated volume rendering and tomographic reconstruction using texture mapping hardware. 1994 Symposium on Volume Visualization, pp. 91-98.Google Scholar
  3. Cruz-Neira C, Sandin D, DeFanti T (1993) Surround-Screen Projection-Based Virtual Reality: The Design and Implementation of the CAVE. Computer Graphics, ACM SIGGRAPH, 135-142.Google Scholar
  4. Darrell T, Wohn K (1988) Pyramid based depth from focus. Proc. CVPR, pp. 504-509.Google Scholar
  5. Ens J, Lawrance P (1993) An Investigation of Methods for Determining Depth from Focus. IEEE Trans. On Pattern Analysis and Machine Intelligence, 15(2):97-108.CrossRefGoogle Scholar
  6. Grossman P (1987) Depth from Focus. Pattern Recognition Letters, 5:63-69, 1987.CrossRefGoogle Scholar
  7. Haykin S (1994) Communication Systems Chap.10. 3rd ed., John Wiley & Sons, Inc.Google Scholar
  8. Horn BKP (1968) Focusing. MIT Artificial Intelligence Laboratory, Memo No. 160.Google Scholar
  9. Jarvis R (1983) A perspective on range-finding techniques for computer vision. IEEE, Trans. Patt. Anal. Machine. Intell, vol. PAMI-3, pp. 122-139.Google Scholar
  10. Lai SH, Fu CW, Chang S (1992) A Generalized Depth Estimation Algorithm with a Single Image. IEEE Trans. On Pattern Analysis and Machine Intelligence, 14(4):405-411.CrossRefGoogle Scholar
  11. Meißner M, Hoffmann U, Straßer W (1999) Enabling classification and shading for 3D texture mapping based volume rendering using OpenGL and extensions. In Proceedings of Visualization 1999, pages 207-214.Google Scholar
  12. Meißner M, Huang J, Bartz D, Mueller K, and Crawfis R (2000) A practical evaluation of popular volume rendering algorithms. In Proceedings of the Symposium on Volume Visualization 2000, pages 81-90.Google Scholar
  13. Nayar SK, Nakagawa Y (1990) Shape form Focus: An Effective Approach for Rough Surfaces. IEEE Intl. Conference on Robotics and Automation, pp. 218-225.Google Scholar
  14. Nayar S.K (1992) Shape from focus system. Proc. CVPR, pp.302-308.Google Scholar
  15. Nayar SK, Walanabe M, Nogouchi M (1995) Real time focus range sensor. Proc. ICCV, pp. 995-1001.Google Scholar
  16. Nayar SK (1992) Shape from Focus System for Rough Surface. In Proc. Image Understanding Workshop, pp. 539-606.Google Scholar
  17. Papoulis A (1991) Probability, Random Variables, and Stochastic Processes Chap.15. 2nd ed., McGrawHill.Google Scholar
  18. Pentland AP (1987) A New Sense of Depth of Field. IEEE Trans. On Pattern Analysis and Machine Intelligence, 9(4):523-531.CrossRefGoogle Scholar
  19. Porter T, Duff T (1984) Compositing Digital Images. In Proceedings of the SIGGRAPH.Google Scholar
  20. Rezk-Salama C, Engel K, Bauer M, Greiner G, Ertl T (2000) Interactive volume rendering on standard PC graphics hardware using multi-textures and multi-stage rasterization. In Proceedings of the Workshop on Graphics Hardware 2000, pages 109-118.Google Scholar
  21. Schechner YY, Kiryati N, Basri R (2000) Separation of Transparent Layers using Focus. International Journal of Computer Vision, 39 (1): 25-39, Kluwer Academic Publishers.MATHCrossRefGoogle Scholar
  22. Subbarao M (1988) Parallel Depth Recovery by Changing Camera Parameters. In Proc. International Conference on Computer Vision, pp. 149-155.Google Scholar
  23. Xiong Y, Shafer SA (1993) Depth from focusing and defocusing. Proc. CVPR, pp. 68-73.Google Scholar
  24. Yeo TTE, Ong S H, Jayasooriah, Sinniah R (1993) Autofocusing for tissue microscopy. Image and, Vision Comp. vol. 11, pp. 629-639.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Sinan Kockara
    • 1
  • Nawab Ali
    • 1
  • Serhan Dagtas
    • 1
  1. 1.Department of Applied ScienceUniversity of Arkansas at Little RockLittle RockUSA

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