Chromosome Research

, 16:523 | Cite as

Spatial quantitative analysis of fluorescently labeled nuclear structures: Problems, methods, pitfalls

  • O. Ronneberger
  • D. Baddeley
  • F. Scheipl
  • P. J. Verveer
  • H. Burkhardt
  • C. Cremer
  • L. Fahrmeir
  • T. Cremer
  • B. Joffe
Open Access
Article

Abstract

The vast majority of microscopic data in biology of the cell nucleus is currently collected using fluorescence microscopy, and most of these data are subsequently subjected to quantitative analysis. The analysis process unites a number of steps, from image acquisition to statistics, and at each of these steps decisions must be made that may crucially affect the conclusions of the whole study. This often presents a really serious problem because the researcher is typically a biologist, while the decisions to be taken require expertise in the fields of physics, computer image analysis, and statistics. The researcher has to choose between multiple options for data collection, numerous programs for preprocessing and processing of images, and a number of statistical approaches. Written for biologists, this article discusses some of the typical problems and errors that should be avoided. The article was prepared by a team uniting expertise in biology, microscopy, image analysis, and statistics. It considers the options a researcher has at the stages of data acquisition (choice of the microscope and acquisition settings), preprocessing (filtering, intensity normalization, deconvolution), image processing (radial distribution, clustering, co-localization, shape and orientation of objects), and statistical analysis.

Key words

confocal microscopy image quantification nucleus preprocessing 

Supplementary material

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Copyright information

© Springer 2008

Authors and Affiliations

  • O. Ronneberger
    • 1
  • D. Baddeley
    • 2
  • F. Scheipl
    • 3
  • P. J. Verveer
    • 4
  • H. Burkhardt
    • 1
  • C. Cremer
    • 2
  • L. Fahrmeir
    • 3
  • T. Cremer
    • 5
    • 6
  • B. Joffe
    • 5
  1. 1.Department of Pattern Recognition and Image ProcessingUniversity of FreiburgFreiburgGermany
  2. 2.Applied Optics and Image Processing Group, Kirchhoff Institute of PhysicsUniversity of HeidelbergHeidelbergGermany
  3. 3.Department of StatisticsLudwig-Maximilian UniversityMunichGermany
  4. 4.Max Planck Institute of Molecular PhysiologyDortmundGermany
  5. 5.Department of Anthropology and Human GeneticsLudwig-Maximilian UniversityMunichGermany
  6. 6.Munich Center for Integrated Protein ScienceMunichGermany

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