A Heuristic Approach to Automatically Segment Signal from Background in DNA Microarray Images

  • S. S. Manjunath
  • Priya Nandihal
  • Lalitha Rangarajan
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 801)


Microarray is an efficacious tool used to detect, analyze and describe local features of the genome in the form of an image. A microarray is glass slide which consists of different nucleic acid inquest added chemically. Microarray provides enough guidance on infection pathology, progression, resistance to treatment, and response to cellular microenvironments and ultimately may lead to improved and innovative approaches for disease diagnosis. Study of microarray includes these steps: initially spot addressing followed by spot separation as background and foreground and finally intensity extraction of separated spots. In the spot separation stage, extended k-means and Fast EM methods are proposed. The proposed method is a heuristic approach where Coefficient-Variation of the input image is used as a metric to switch the image for segmentation to the appropriate existing method as well as to the proposed method to efficiently segment the foreground signals from the background in existence of undetermined or unwanted pixel values, and inadequately articulated spots in DNA microarray images. Experimental results and analysis of proposed methods shows promising results when compared with existing methods in the literature.


Microarray experiment Expectation maximization K-means Segmentation 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Dayananda Sagar Academy of Technology and ManagementBangaloreIndia
  2. 2.University of MysoreMysoreIndia

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