Mean shift and morphology based segmentation scheme for DNA microarray images

  • Authors:
  • Shuanhu Wu;Chuangcun Wang;Hong Yan

  • Affiliations:
  • School of Computer Science & Technology, Yantai University, Yantai, China;School of Computer Science & Technology, Yantai University, Yantai, China;Department of Computer Engineering and Information Technology, City University of HongKong, Kowloon, Hong Kong

  • Venue:
  • ICIC'05 Proceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part II
  • Year:
  • 2005

Quantified Score

Hi-index 0.00

Visualization

Abstract

Image segmentation is supposed to be the most important step in microarray image analysis. In this work, we proposed a new template-based segmentation method for DNA microarray images. Different from the local-based segmentation techniques adopted by all the available analysis softwares, our algorithm segments images from global view of point. Based on mean shift filtering technique, we first segmented image into some different homogenous regions in which all the spots appeared as different local maximum regions. Then an initial spot segmentation template was extracted by morphological H- reconstruction. Finally, a refined spot segmentation template was obtained by histogram analysis. Experimental results showed that our algorithm is robust and can obtain accurate spot segmentation results. Especially, compared to all the available algorithms, our template-based spot segmentation scheme not only can facilitate downstream intensity extraction step but also can be very helpful to improve the accuracy of intensity extraction.