Computer - Based Image Analysis for Histochemistry

  • Gustav Bernroider


A large variety of imaging methods has been developed to address the location and quantification of signals emerging from a place coded distribution of biological activity. The key question addressed by all such techniques is the extraction of cellular or molecular attributes from image coded information. This requires multiple calibration steps that gradually associate biological attributes with images. In the following text, major requirements or calibration steps that must be met to infer physico-chemical aspects from the space-coded intensity distribution provided by images are outlined. Also included is a comparison between traditional transmission images from radiographic receptor binding and novel approaches using intrinsic emission tomographs from enzyme-labeled ligands. Another major point is that computer-assisted manipulations of images allow the construction of “coincident images” that can combine such diverse signals as low light emissions with high-level light transmission images. Demonstrative examples from neuro-imaging show that coincident images can provide multiple histochemical information in a global, yet spatially selective way.


Light Emission Optical Density Physical Section Receptor Autoradiography Channel Electron Multiply 
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.


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Copyright information

© Springer Science+Business Media New York 1994

Authors and Affiliations

  • Gustav Bernroider
    • 1
  1. 1.Institute of ZoologyUniversity of SalzburgSalzburgAustria

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