• DocumentCode
    3146186
  • Title

    MR Image Segmentation Based on Modified Ant Colony Algorithm

  • Author

    Luo, W.M. ; Liu, W.W. ; Chen, Y.W. ; Shen, Z.W. ; Wu, R.H. ; Huang, J.X. ; Qiu, Q.C.

  • Author_Institution
    Eng. Coll., Shantou Univ., Shantou, China
  • fYear
    2010
  • fDate
    18-20 June 2010
  • Firstpage
    1
  • Lastpage
    3
  • Abstract
    Magnetic resonance imaging (MRI) is a widely used method to obtain high quality medical image of the brain. Post-processing MR images with segmentation algorithms enhances the visualization and measurement of soft tissues and lesions. However, the conventional algorithms are not perfect and there are still some regions which are not partitioned accurately. In this paper, a new ant colony algorithm is presented in accordance with the defect of previous variety and stagnation. The contrast experimental results show that the new algorithm is not only of higher segmentation quality but also of higher computational speed, and prove that the algorithm is efficient and superior.
  • Keywords
    biological tissues; biomedical MRI; brain; image segmentation; medical image processing; MR image post-processing; MR image segmentation; brain; computational speed; lesions; magnetic resonance imaging; modified ant colony algorithm; soft tissues; stagnation; visualization; Biomedical engineering; Biomedical imaging; Clustering algorithms; Educational institutions; Evolutionary computation; Image segmentation; Magnetic resonance imaging; Partitioning algorithms; Robustness; Visualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedical Engineering (iCBBE), 2010 4th International Conference on
  • Conference_Location
    Chengdu
  • ISSN
    2151-7614
  • Print_ISBN
    978-1-4244-4712-1
  • Electronic_ISBN
    2151-7614
  • Type

    conf

  • DOI
    10.1109/ICBBE.2010.5517746
  • Filename
    5517746