Processing of Microarray Images

  • Fernando Mastandrea
  • Álvaro Pardo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5856)

Abstract

In this paper we present the results of a system for processing microarray images which includes the gridding and spot detection steps. The main goal of this work is to develop automatic methods to process microarray images including confidence measures on the results. The gridding step is based on the method proposed in [1] and improves it by the automatic determination of the grid parameters, and a more precise orientation detection. For spot detection the algorithm uses the Number of False Alarms methodology [2] which can be used to finely adjust the spot position and provides a confidence measure on the detection. We test the results obtained by our method with simulated images against existing microarray software.

Keywords

True Positive Spot Center Spot Detection Gridding Step Microarray Image 
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.

References

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    Desolneux, A., Moisan, L., Morel, J.-M.: From Gestalt Theory to Image Analysis: A Probabilistic Approach. Springer, Heidelberg (2008)CrossRefGoogle Scholar
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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Fernando Mastandrea
    • 1
  • Álvaro Pardo
    • 1
  1. 1.Department of Electrical EngineeringUniversidad Católica del Uruguay 

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