• DocumentCode
    2200358
  • Title

    Medical Image Retrieval Algorithm Using Setting Up Weight Automatically

  • Author

    Zhang, Qidong ; Gao, Liqun

  • Author_Institution
    Sch. of Inf. Sci. & Eng., Shenyang Ligong Univ., Shenyang, China
  • fYear
    2010
  • fDate
    1-3 Nov. 2010
  • Firstpage
    60
  • Lastpage
    63
  • Abstract
    Integrating multiple features content-based image retrieval can overcome the problems of single feature, but how to combine these features and feature representation methods is important in image retrieval. In this paper an image feature retrieval setting up weight automatically based on particle swarm optimization algorithm is proposed, which could guide the movement direction for particles, and close to ideal solution set quickly. Considering the characteristics of medical image, the contour let transform is used for texture feature extraction. Zernike moments extracts shape feature. The experimental results show that the recall and precision of this proposed approach is better. It can get the best feature combination for medical image retrieval.
  • Keywords
    content-based retrieval; feature extraction; image retrieval; image texture; medical image processing; particle swarm optimisation; transforms; Zernike moments; content-based image retrieval; contourlet transform; feature representation methods; medical image retrieval algorithm; particle swarm optimization; setting up weight automatically; shape feature extraction; texture feature extraction; Medical Image Retrieval; Particle Swarm Optimization; Setting up Weight Automatically;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Networks and Intelligent Systems (ICINIS), 2010 3rd International Conference on
  • Conference_Location
    Shenyang
  • Print_ISBN
    978-1-4244-8548-2
  • Electronic_ISBN
    978-0-7695-4249-2
  • Type

    conf

  • DOI
    10.1109/ICINIS.2010.173
  • Filename
    5693679