Computational Framework for Simulating Fluorescence Microscope Images With Cell Populations

  • Lehmussola A
  • Ruusuvuori P
  • Selinummi J
 et al. 
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Fluorescence microscopy combined with digital imaging constructs a basic platform for numerous biomedical studies in the field of cellular imaging. As the studies relying on analysis of digital images have become popular, the validation of image processing methods used in automated image cytometry has become an important topic. Especially, the need for efficient validation has arisen from emerging high-throughput microscopy systems where manual validation is impractical. We present a simulation platform for generating synthetic images of fluorescence-stained cell populations with realistic properties. Moreover, we show that the synthetic images enable the validation of analysis methods for automated image cytometry and comparison of their performance. Finally, we suggest additional usage scenarios for the simulator. The presented simulation framework, with several user-controllable parameters, forms a versatile tool for many kinds of validation tasks, and is freely available at

Author-supplied keywords

  • Algorithms
  • Cells, Cultured
  • Computer Simulation
  • Image Enhancement
  • Image Interpretation, Computer-Assisted
  • Microscopy, Fluorescence
  • Models, Biological
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Software
  • Software Validation
  • automated image cytometry
  • biological techniques
  • biomedical optical imaging
  • cellular biophysics
  • cellular imaging
  • digital image analysis
  • fluorescence
  • fluorescence microscopy
  • fluorescence-stained cell population
  • high-throughput microscopy system
  • image processing
  • medical image processing
  • optical microscopy

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  • A Lehmussola

  • P Ruusuvuori

  • J Selinummi

  • H Huttunen

  • O Yli-Harja

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