The Collection, Processing, and Display of Digital Three-Dimensional Images of Biological Specimens

  • Hans Chen
  • Jason R. Swedlow
  • Marcus Grote
  • John W. Sedat
  • David A. Agard

Abstract

In general, the study and analysis of biological structure requires a three-dimensional (3D) imaging capability. Dramatic technical advances have now made it possible to record 3D microscopic images of biological specimens using either electron or light microscopy. While the collection of 3D data sets has now become routine, the analysis and interpretation of these images generally require significant time and effort. This is true, in part, because each type of image seems to require a specific set of processing algorithms and parameters. In addition, the software tools required for extracting useful information from the resulting complicated multidimensional data sets (e.g., three spatial dimensions, time, different components) are not completely developed. Computational image processing provides a powerful approach for reducing the systematic errors present in any 3D data set and enhancing the clarity and contrast of relevant features.

Keywords

Shared Memory Volume Rendering Biological Specimen Image Overlay Howard Hughes Medical Institute 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Agard, D.A., Hiraoka, Y., Shaw, P., and Sedat, J.W., 1989, Fluorescence microscopy in three dimensions, Methods Cell Biol. 30:353–377.PubMedCrossRefGoogle Scholar
  2. Aikens, R.S., Agard, D.A., and Sedat, J.W., 1989, Solid-state imagers for microscopy, Methods Cell Biol. 29:291–313.PubMedCrossRefGoogle Scholar
  3. Andrews, H.C., Tescher, A.G., and Kruger, R.P., 1972, Image processing by digital computer, IEEE Spect. 9:20–32.CrossRefGoogle Scholar
  4. Bui-Tuong, P., 1975, Illumination for computer generated pictures, CACM June:311–317.Google Scholar
  5. Castleman, K.R., 1979, Digital Image Processing, Prentice-Hall, Englewood Cliffs, New Jersey.Google Scholar
  6. Cline, H.E., Lorensen, W.E., Ludke, S., Crawford, C.R., and Teeter, B.C., 1988, Two algorithms for the three-dimensional reconstruction of tomograms, Med. Phys. 15:320–327.PubMedCrossRefGoogle Scholar
  7. Dreibin, R.A., Carpenter, L., and Hanranhan, P., 1988, Volume rendering, Computer Graphics 22:65–75.CrossRefGoogle Scholar
  8. Gibson, S.F., and Lanni, F., 1991, Experimental test of an analytical model of aberration in an oil-immersion objective lens used in three-dimensional light microscopy, J. Opt. Soc. Am. 8:1601–1613.CrossRefGoogle Scholar
  9. Giloh, H., and Sedat, J.W., 1982, Fluorescence microscopy: Reduced pho-tobleaching of rhodamine and fluorescein protein conjugates by n-propyl gallate, Science 217:1252–1255.PubMedCrossRefGoogle Scholar
  10. Hell, S., Reiner, G., Cremer, C., and Stelzer, E.H.K., 1993, Aberrations in confocal fluorescence microscopy induced by mismatches in refractive index, J. Microsc. 169:391–405.CrossRefGoogle Scholar
  11. Highett, M.I., Beven, A.F., and Shaw, P.J., 1993, Localization of 5 S genes and transcripts in Pisum sativum nuclei, J. Cell Sci. 105:1151–1158.PubMedGoogle Scholar
  12. Hiraoka, Y., Sedat, J., and Agard, D., 1987, The use of a charge coupled device for quantitative optical microscopy of biological structures, Science 238:36–41.PubMedCrossRefGoogle Scholar
  13. Hiraoka, Y., Minden, J.S., Swedlow, J.R., Sedat, J.W., and Agard, D.A., 1989, Focal points for chromosome condensation and decondensation revealed by three-dimensional in vivo time-lapse microscopy, Nature 342:293–296.PubMedCrossRefGoogle Scholar
  14. Hiraoka, Y., Sedat, J.W., and Agard, D.A., 1990, Determination of three-dimensional imaging properties of a light microscope system, Biophys. J. 57:325–333.PubMedCrossRefGoogle Scholar
  15. Hiraoka, Y., Swedlow, J.R., Paddy, M.R., Agard, D.A., and Sedat, J.W., 1991, Three-dimensional multiple-wavelength fluorescence microscopy for the structural analysis of biological phenomena, Semin. Cell Biol. 2:153–165.PubMedGoogle Scholar
  16. Huang, T.S., Yang, G.J., and Tang, G.Y., 1979, A fast two-dimensional median filtering algorithm, IEEE Trans. Acoust. Speech Sig. Proc. 27:13–18.CrossRefGoogle Scholar
  17. Kam, Z., Jones, M.O., Chen, H., Agard, D.A., and Sedat, J.W., 1993, Design and construction of an optimal illumination system for quantitative wide-field multi-dimensional microscopy, Bioimaging 1:71–81.CrossRefGoogle Scholar
  18. Kaufman, A., 1991, Volume Visualization, IEEE Computer Society Press, Los Alamitos, California.Google Scholar
  19. Narendra, P.M., 1981, A separable median filter for image noise smoothing, IEEE Trans. Pat. Anal. Mach. Intel. 3:20–29.CrossRefGoogle Scholar
  20. Neider, J.A., and Mead, R., 1965, A simplex method for function minimization, Computer J. 7:308–313.CrossRefGoogle Scholar
  21. Parkinson, J.M., and Hutchison, D., 1972, An investigation into the efficiency of variants of the simplex method. In: Numerical Methods for Nonlinear Optimization, Academic Press, London.Google Scholar
  22. Pawley, J.B., 1994, The sources of noise in three-dimensional microscopical data sets. In: Three Dimensional Confocal Microscopy: Volume Investigation of Biological Specimens (J. Stevens, ed.), Academic Press, San Diego, pp. 47–94.CrossRefGoogle Scholar
  23. Pratt, W.K., 1978, Digital Image Processing, John Wiley &; Sons, New York.Google Scholar
  24. Russ, J.C., 1992, The Image Processing Handbook, CRC Press, Boca Raton, Florida.Google Scholar
  25. Shaw, P.J., Agard, D.A., Hiraoka, Y., and Sedat, J.W., 1989, Tilted view reconstruction in optical microscopy. Three-dimensional reconstruction of Drosophila melanogaster embryo nuclei, Biophys. J. 55:101–110.Google Scholar
  26. Sullivan, W., Minden, J.S., and Alberts, B.M., 1990, daugtherless abo-like, a Drosophila maternal-effect mutation that exhibits abnormal centrosome separation during the late blastoderm divisons, Development 110:311–323.PubMedGoogle Scholar
  27. Swedlow, J.R., Sedat, J.W., and Agard, D.A., 1993, Multiple chromosomal populations of topoisomerase II detected in vivo by time-lapse, three-dimensional wide field microscopy, Cell 73:97–108.PubMedCrossRefGoogle Scholar
  28. Tsien, R.Y., and Waggoner, A., 1990, Fluorophores for confocal microscopy: Photophysics and photochemistry. In: Handbook of Biological Confocal Microscopy (J.B. Pawley, ed.), Plenum Press, New York, pp. 169–178.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 1995

Authors and Affiliations

  • Hans Chen
    • 1
  • Jason R. Swedlow
    • 2
  • Marcus Grote
    • 3
  • John W. Sedat
    • 1
  • David A. Agard
    • 1
  1. 1.Department of Biochemistry and Biophysics, Howard Hughes Medical InstituteUniversity of California at San FranciscoSan FranciscoUSA
  2. 2.Graduate Group in Biophysics, Howard Hughes Medical InstituteUniversity of California at San FranciscoSan FranciscoUSA
  3. 3.Scientific Computing and Computational Mathematics ProgramStanford UniversityStanfordUSA

Personalised recommendations