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Low-complexity PDE-based approach for automatic microarray image processing

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Abstract

Microarray image processing is known as a valuable tool for gene expression estimation, a crucial step in understanding biological processes within living organisms. Automation and reliability are open subjects in microarray image processing, where grid alignment and spot segmentation are essential processes that can influence the quality of gene expression information. The paper proposes a novel partial differential equation (PDE)-based approach for fully automatic grid alignment in case of microarray images. Our approach can handle image distortions and performs grid alignment using the vertical and horizontal luminance function profiles. These profiles are evolved using a hyperbolic shock filter PDE and then refined using the autocorrelation function. The results are compared with the ones delivered by state-of-the-art approaches for grid alignment in terms of accuracy and computational complexity. Using the same PDE formalism and curve fitting, automatic spot segmentation is achieved and visual results are presented. Considering microarray images with different spots layouts, reliable results in terms of accuracy and reduced computational complexity are achieved, compared with existing software platforms and state-of-the-art methods for microarray image processing.

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Acknowledgments

This work was supported by the European Social Fund through the POSDRU Program, DMI 1.5, ID 137516-PARTING.

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Authors and Affiliations

  1. Department of Mass Spectrometry, Chromatography and Applied Physics, National Institute for Research and Development of Isotopic and Molecular Technologies, Cluj-Napoca, Romania

    Bogdan Belean & Adrian Bot

  2. Department of Communications, Technical University of Cluj-Napoca, Cluj-Napoca, Romania

    Bogdan Belean & Romulus Terebes

Authors
  1. Bogdan Belean
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  2. Romulus Terebes
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  3. Adrian Bot
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Correspondence to Bogdan Belean.

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Belean, B., Terebes, R. & Bot, A. Low-complexity PDE-based approach for automatic microarray image processing. Med Biol Eng Comput 53, 99–110 (2015). https://doi.org/10.1007/s11517-014-1214-2

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  • DOI: https://doi.org/10.1007/s11517-014-1214-2

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