Effective Quantification of Gene Expression Levels in Microarray Images Using a Spot-Adaptive Compound Clustering-Enhancement-Segmentation Scheme

  • Antonis Daskalakis
  • Dionisis Cavouras
  • Panagiotis Bougioukos
  • Spiros Kostopoulos
  • Pantelis Georgiadis
  • Ioannis Kalatzis
  • George Kagadis
  • George Nikiforidis
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4707)


A spot-adaptive compound clustering-enhancement-segmentation (CES) scheme was developed for the quantification of gene expression levels in microarray images. The CES-scheme employed 1/griding, for locating spot-regions, 2/Fuzzy C-means clustering, for segmenting spots from background, 3/ background noise estimation and spot’s center localization, 4/emphasizing of spot’s outline by the CLAHE image enhancement technique, 5/segmentation by the SRG algorithm, using information from step 3, and 6/microarray spot intensity extraction. Extracted intensities by the CES-Scheme were compared against those obtained by the MAGIC TOOL’s SRG. Kullback-Liebler metric’s values for the CES-Scheme were on average double than MAGIC TOOL’s, with differences ranging from 1.45bits to 2.77bits in 7 cDNA images. Coefficient-of-Variation results showed significantly higher reproducibility (p<0.001) for the CES-Scheme in quantifying gene expression levels. Processing times for 1024x1024 16-bit microarray images containing 6400 spots were 300 and 487 seconds for the CES-Scheme and MAGIC TOOL respectively.


DNA microarray image analysis microarray griding CLAHE SRG 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Antonis Daskalakis
    • 1
  • Dionisis Cavouras
    • 2
  • Panagiotis Bougioukos
    • 1
  • Spiros Kostopoulos
    • 1
  • Pantelis Georgiadis
    • 1
  • Ioannis Kalatzis
    • 2
  • George Kagadis
    • 1
  • George Nikiforidis
    • 1
  1. 1.Department of Medical Physics, School of Medicine, University of Patras, Rio, GR-26500Greece
  2. 2.Medical Signal and Image Processing Lab, Department of Medical Instruments Technology, Technological Educational Institute of Athens, Ag. Spyridonos Street, Aigaleo, 122 10, AthensGreece

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