• DocumentCode
    2707958
  • Title

    Research on indexing in medical image database retrieval using self-organizing maps

  • Author

    Hao Zou ; Jian Sun

  • Author_Institution
    Sino-Dutch Biomed. & Inf. Eng. Sch., Northeastern Univ., Shenyang, China
  • fYear
    2012
  • fDate
    6-8 June 2012
  • Firstpage
    950
  • Lastpage
    955
  • Abstract
    High dimensional indexing scheme is a significant research issue for content-based image retrieval in medical image database. The SOM-based approach proposed in this paper uses a Kernel Density Estimation Method (Mean Shift) to describe for medical image database, which fits the complex data distribution reasonably well. And this approach trains optimized SOM network to partition data space. Experiments on a real-world medical image dataset demonstrate a good topology configuration of the data and a remarkable reduction of the amount of accessed vectors in exact NN searches compare with existing indexing schemes.
  • Keywords
    content-based retrieval; estimation theory; image retrieval; indexing; medical image processing; self-organising feature maps; visual databases; SOM-based approach; content-based image retrieval; high dimensional indexing; kernel density estimation method; mean shift; medical image database retrieval; self-organizing maps; Biomedical imaging; Data models; Estimation; Indexing; Kernel; Vectors; Content-based medical image retrieval; SOM; data distribution model; high-dimensional indexing scheme;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information and Automation (ICIA), 2012 International Conference on
  • Conference_Location
    Shenyang
  • Print_ISBN
    978-1-4673-2238-6
  • Electronic_ISBN
    978-1-4673-2236-2
  • Type

    conf

  • DOI
    10.1109/ICInfA.2012.6246953
  • Filename
    6246953