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Automatic Grid Fitting for Genetic Spot Array Images Containing Guide Spots

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Computer Analysis of Images and Patterns (CAIP 1999)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1689))

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Abstract

In the domain of biotechnology array-based methods are used to gain rapid access to genetic information based on the signals of the individual array elements (spots). For an automated analysis of the spots it is necessary to fit a grid to the spots in the digital image in order to represent the array distortions that may occur in the course of the experiment. In order to make the grid fitting problem tractable in a certain class of experiments spot arrays contain a sub-grid of guide spots with a known signal characteristic. We present an automatic grid fitting method for spot array images containing guide spots. Our approach uses simple image processing methods and takes into account prior knowledge inherent in the imaging process.

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References

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Author information

Authors and Affiliations

  1. Pattern Recognition and Image Processing Group, Vienna University of Technology, Treitlstr. 3/1832, A-1040, Vienna, Australia

    Norbert Brändle & Horst Bischof

  2. Novartis Forschungsinstitut Genetics, Brunner Str. 59, A-1230, Vienna, Australia

    Hilmar Lapp

Authors
  1. Norbert Brändle
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  2. Hilmar Lapp
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  3. Horst Bischof
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Editor information

Editors and Affiliations

  1. Faculty of Computer and Information Science, Tržaška cesta 25, 1001, Ljubljana, Slovenia

    Franc Solina  & Alešs Leonardis  & 

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© 1999 Springer-Verlag Berlin Heidelberg

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Brändle, N., Lapp, H., Bischof, H. (1999). Automatic Grid Fitting for Genetic Spot Array Images Containing Guide Spots. In: Solina, F., Leonardis, A. (eds) Computer Analysis of Images and Patterns. CAIP 1999. Lecture Notes in Computer Science, vol 1689. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48375-6_43

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  • DOI: https://doi.org/10.1007/3-540-48375-6_43

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66366-9

  • Online ISBN: 978-3-540-48375-5

  • eBook Packages: Springer Book Archive

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