A data-adaptive approach to cDNA microarray image enhancement

  • Authors:

  • Rastislav Lukac;Konstantinos N. Plataniotis;Bogdan Smolka;Anastasios N. Venetsanopoulos

  • Affiliations:

  • The Edward S. Rogers Sr. Dept. of Electrical and Computer Engineering, University of Toronto, Toronto, Canada;The Edward S. Rogers Sr. Dept. of Electrical and Computer Engineering, University of Toronto, Toronto, Canada;Polish-Japanese Institute of Information Technology, Warsaw, Poland;The Edward S. Rogers Sr. Dept. of Electrical and Computer Engineering, University of Toronto, Toronto, Canada

  • Venue:
  • ICCS'05 Proceedings of the 5th international conference on Computational Science - Volume Part II
  • Year:
  • 2005

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Abstract

A data-adaptive approach for cDNA microarray image enhancement is presented. Through the weighting coefficients adaptively determined from local microarray image statistics, the proposed technique tunes the overall filter's detail-preserving and noise-attenuating characteristics and uses both the spatial and spectral correlation of the cDNA image during processing. Noise removal is performed by tuning a membership function which utilizes the aggregated absolute differences between the cDNA microarray inputs localized within a processing window sliding over the image.