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3D Reconstruction of Confocal Image Data

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Abstract

The main advantage of the confocal microscope is often said to be the ability to produce serial optical sections of fluorescent samples, ultimately for the purpose of reconstructing microscopic objects in three dimensions (Carlsson and Aslund 1987). There are many ways, and reasons, to reconstruct confocal image data. As an example, consider the sample of embryonic mouse heart shown in Fig. 10.1 reconstructed using a variety of three-dimensional (3D) techniques. This chapter will introduce these methods and discuss topics such as (a) why one might want to undertake this task, (b) some definitions of the representation of 3D space using images, (c) the different types of 3D representations that can be made, and (d) the necessary steps to make useful reconstructions. Along the way, the limitations and potential pitfalls that arise will be discussed.

Keywords

3D reconstruction Image contrast Histogram Pixel Resolution Segmentation Volume render Voxel 

References

  1. Biggs, D.S., 3D deconvolution microscopy. Curr Protoc Cytom, 2010. Chapter 12: p. Unit 12 19 1–20.Google Scholar
  2. Biggs, D.S.C., Clearing up deconvolution. Biophotonics International, 2004(February): p. 32–37.Google Scholar
  3. Carlsson, K. and N. Aslund, Confocal imaging for 3-D digital microscopy. Appl. Opt., 1987. 26(16): p. 3232–3238.Google Scholar
  4. Clendenon, J.L., J.M. Byars, and D.P. Hyink, Image processing software for 3D light microscopy. Nephron Exp Nephrol, 2006. 103(2): p. e50–4.Google Scholar
  5. Feng, D., D. Marshburn, D. Jen, R.J. Weinberg, R.M. Taylor, II, and A. Burette. Stepping into the third dimension. J Neurosci, 2007. 27(47): p. 12757–60.Google Scholar
  6. Guan, Y.Q., Y.Y. Cai, X. Zhang, Y.T. Lee, M. Opas. Adaptive correction technique for 3D reconstruction of fluorescence microscopy images. Microsc Res Tech, 2008. 71(2): p. 146–57.Google Scholar
  7. Hecksher-Sorensen, J. and J. Sharpe, 3D confocal reconstruction of gene expression in mouse. Mech Dev, 2001. 100(1): p. 59–63.Google Scholar
  8. Lee, S.C. and P. Bajcsy, Intensity correction of fluorescent confocal laser scanning microscope images by mean-weight filtering. J Microsc, 2006. 221(Pt 2): p. 122–36.Google Scholar
  9. Lin, G., U. Adiga, K. Olson, J.F. Guzowski, C.A. Barnes, and B. Roysam A hybrid 3D watershed algorithm incorporating gradient cues and object models for automatic segmentation of nuclei in confocal image stacks. Cytometry A, 2003. 56(1): p. 23–36.Google Scholar
  10. Losavio, B.E., Y. Liang, A. Santamaría-Pang, I.A. Kakadiaris, C.M. Colbert, and Peter Saggau, Live neuron morphology automatically reconstructed from multiphoton and confocal imaging data. J Neurophysiol, 2008. 100(4): p. 2422–9.Google Scholar
  11. Mackenzie, J.M., M.G. Burke, T. Carvalho and A. Eades. Ethics and digital imaging. Microscopy Today, 2006. 14(1): p. 40–41.Google Scholar
  12. McNally, J.G., T.S. Karpova, J.A.Cooper, J.-A. Conchello. Three-dimensional imaging by deconvolution microscopy. Methods, 1999. 19(3): p. 373–85.Google Scholar
  13. Rodriguez, A., D. Ehlenberger, K. Kelliher, M. Einstein, S.C. Henderson, J.H. Morrison, P.R. Hof and S.L. Wearne, Automated reconstruction of three-dimensional neuronal morphology from laser scanning microscopy images. Methods, 2003. 30(1): p. 94–105.Google Scholar
  14. Rueden, C.T. and K.W. Eliceiri, Visualization approaches for multidimensional biological image data. Biotechniques, 2007. 43(1 Suppl): p. 31, 33–6.Google Scholar
  15. Ruthensteiner, B. and M. Hess, Embedding 3D models of biological specimens in PDF publications. Microsc Res Tech, 2008. 71(11): p. 778–86.Google Scholar
  16. Savio-Galimberti, E., J. Frank, M. Inoue, J.I. Goldhaber, M.B. Cannell, J.H.B. Bridge, and F.B. Sachse. Novel features of the rabbit transverse tubular system revealed by quantitative analysis of three-dimensional reconstructions from confocal images. Biophys J, 2008. 95(4): p. 2053–62.Google Scholar
  17. Soufan, A.T., G. van den Berg, P.D. Moerland, M.M.G. Massink, M.J.B. van den Hoff, A.F.M. Moorman and J.M. Ruijter. Three-dimensional measurement and visualization of morphogenesis applied to cardiac embryology. J Microsc, 2007. 225(Pt 3): p. 269–74.Google Scholar
  18. Sun, Y., B. Rajwa, and J.P. Robinson, Adaptive image-processing technique and effective visualization of confocal microscopy images. Microsc Res Tech, 2004. 64(2): p. 156–63.Google Scholar
  19. Yi, Q. and M.G. Coppolino, Automated classification and quantification of F-actin-containing ruffles in confocal micrographs. Biotechniques, 2006. 40(6): p. 745–6, 748, 750 passim.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Department of Regenerative Medicine and Cell BiologyMedical University of South CarolinaCharlestonUSA

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