Intelligent spot detection for 2-DE gel image

  • Authors:

  • Yi-Sheng Liu;Shu-Yuan Chen;Ya-Ting Chao;Ru-Sheng Liu;Yuan-Ching Tsai;Jaw-Shu Hsieh

  • Affiliations:

  • Department of Computer Science and Engineering, Yuan Ze University, Chung Li, Taiwan;Department of Computer Science and Engineering, Yuan Ze University, Chung Li, Taiwan;Department of Computer Science and Engineering, Yuan Ze University, Chung Li, Taiwan;Department of Computer Science and Engineering, Yuan Ze University, Chung Li, Taiwan;Department of Agronomy, National Taiwan University, Taipei, Taiwan;Department of Agronomy, National Taiwan University, Taipei, Taiwan

  • Venue:
  • PSIVT'06 Proceedings of the First Pacific Rim conference on Advances in Image and Video Technology
  • Year:
  • 2006

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Abstract

In this study, a novel method for spot detection is proposed with the addition of confidence evaluation for each detected spot. The confidence of a spot will give useful hints for subsequent processing such as landmark selection, spot quantification, gel image registration, etc. The proposed method takes slices of a gel image in the gray level direction and build them into a slice tree, which in turn is used to perform spot detection and confidence evaluation. Moreover, the proposed method is fast. Building slice tree for a gel image of 1262×720 take about 3.2 sec. Spot detection take about 66 ms after the slice tree was built. Experimental results show that confidence values are close to subjective judgement.