• DocumentCode
    2086317
  • Title

    Image segmentation of MRI based on improved anttree clustering algorithm

  • Author

    Chenling, Li ; Wenhua, Zeng ; Jiahe, Zhuang

  • Author_Institution
    Key Lab. for Intell. Inf. Technol. of Fujian Province, Xiamen Univ., Xiamen, China
  • Volume
    1
  • fYear
    2008
  • fDate
    17-19 Nov. 2008
  • Firstpage
    1208
  • Lastpage
    1213
  • Abstract
    In this paper, an improved method is proposed based on AntTree clustering algorithm to deal with MRI image. This algorithm uses a new tree-structure model to accelerate the calculation and combines greedy algorithm to update the cluster centre. Compared with K-means and FCM algorithms, the results in the experiment show that the improved AntTree clustering algorithm is a better method in image segmentation of MRI and it also significantly improves the clustering process.
  • Keywords
    greedy algorithms; image segmentation; magnetic resonance imaging; trees (mathematics); MRI; anttree clustering algorithm; greedy algorithm; image segmentation; Clustering algorithms; Greedy algorithms; Image segmentation; Intelligent systems; Knowledge engineering; Magnetic resonance imaging; Partitioning algorithms; Path planning; Process planning; Software algorithms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent System and Knowledge Engineering, 2008. ISKE 2008. 3rd International Conference on
  • Conference_Location
    Xiamen
  • Print_ISBN
    978-1-4244-2196-1
  • Electronic_ISBN
    978-1-4244-2197-8
  • Type

    conf

  • DOI
    10.1109/ISKE.2008.4731114
  • Filename
    4731114
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2086317