Intermediate Computations of Reconstructed Data

  • Joseph J. Capowski


The three preceding chapters have covered the entering of anatomic data into the memory of the computer. This computer-stored data may not model the original structure in the tissue as closely as you want because of histological, optical, and operator-related reasons. The tissue must be cut into sections thin enough to be viewed, one at a time, through a microscope. Consequently, some sort of reassembly process must be performed to align and reconnect the pieces entered from individual sections. Researchers experience numerous hurdles in the reconstruction process. The tissue sections may shrink and wrinkle, so the data recorded may not faithfully represent the original structures as they exist in vivo. Readings from the focus axis of a microscope are usually foreshortened because of unwanted refraction in its optical system. Shrinkage, wrinkling, and foreshortening result in coordinate errors that may be corrected by computer algorithms. A human operator entering data will make mistakes, even when using a well-designed anatomic recording system, and he may not detect some of them until the data have all been entered. Thus, a facility for error detection and correction must be provided. This chapter provides techniques to correct these errors in the computer-stored data in order to generate a data base that faithfully represents the original structure. These techniques are intermediate, for they are performed after the data are collected but before they are used for display and statistical summarization.


Tissue Section Branch Point Binary Tree Dendritic Tree Rotational Alignment 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

For Further Reading

  1. Glaser, E. M. (1982). Snell’s law: The bane of computer microscopists. J. Neurosci. Methods 5: 201–202.PubMedCrossRefGoogle Scholar
  2. Johnson, E. M., and J. J. Capowski (1985). Principles of reconstruction and three-dimensional display of serial sections using a computer. In: The Microcomputer in Cell and Neurobiology Research ( R. R. Mize, ed.). New York: Elsevier, pp. 249–263.Google Scholar
  3. Uylings, H. B. M., C. G. Van Eden, and M. A. Hofman (1986b). Morphometry of size/volume variables and comparison of their bivariate relations in the nervous system under different conditions. J. Neurosci. Methods 18: 19–37.PubMedCrossRefGoogle Scholar
  4. Katz, L., and C. Levinthal (1972). Interactive computer graphics and representation of complex biological structures. Ann. Rev. Biophys. Bioeng. 1: 465–504.CrossRefGoogle Scholar
  5. McInroy, J. L., and J. J. Capowski (1977). A graphics subroutine package for the neuroscience display processor. Comput. Graphics 11 (1): 1–12.CrossRefGoogle Scholar
  6. Buskirk, D. R. (1978). Computer analysis of dendritic morphology. Brain Theor. Newsl. 3: 184–186.Google Scholar
  7. Glaser, E. M. (1981). A binary identification system for use in tracing and analyzing dichotomously branching dendrite and axon systems. Comput. Biol. Med. 11: 17–19.PubMedCrossRefGoogle Scholar
  8. Triller, A., and H. Korn (1986). Variability of axonal arborizations hides simple rules of construction: A topological study from HRP intracellular injections. J. Comp. Neurol. 253: 500–513.PubMedCrossRefGoogle Scholar
  9. Uylings, H. B. M., A. Ruiz-Marcos. and J. van Pelt (1986a). The metric analysis of three-dimensional dendritic tree patterns: A methodological review. J. Neurosci. Methods 18: 127–151.Google Scholar

Copyright information

© Plenum Press, New York 1989

Authors and Affiliations

  • Joseph J. Capowski
    • 1
    • 2
  1. 1.Eutectic Electronics, Inc.RaleighUSA
  2. 2.The University of North CarolinaChapel HillUSA

Personalised recommendations