• DocumentCode
    2665434
  • Title

    Comparison of Two Methods for Automatic Segmentation of Brain MRI Based on 2D Seed Growth and Two Stage FCM Algorithm

  • Author

    Shanthi, K.J. ; Kumar, M. Sasi ; Keshavdas, C.

  • Author_Institution
    Dept. of Electron. & Comm., Sree Chitra Thirunal Coll. of Eng., Trivandrum, India
  • fYear
    2008
  • fDate
    10-12 Dec. 2008
  • Firstpage
    1059
  • Lastpage
    1064
  • Abstract
    Automatic segmentation of brain MRI helps in the volumetric analysis of human brain. Segmentation results in extraction of the different cortical tissues from the slices of the T1 weighted MR brain I mages. Volumetric analysis helps in the early diagnosis of many neural disorders. We have discussed the two different approaches for the segmentation and a comparative analysis of the two methods are discussed.
  • Keywords
    biomedical MRI; brain; feature extraction; fuzzy set theory; image segmentation; medical image processing; 2D seed growth; MR brain images; brain MRI automatic segmentation; cortical tissue extraction; human brain volumetric analysis; neural disorders; Biomedical imaging; Educational institutions; Filters; Fuzzy neural networks; Image processing; Image segmentation; Magnetic resonance imaging; Medical diagnostic imaging; Pixel; Skull;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence for Modelling Control & Automation, 2008 International Conference on
  • Conference_Location
    Vienna
  • Print_ISBN
    978-0-7695-3514-2
  • Type

    conf

  • DOI
    10.1109/CIMCA.2008.171
  • Filename
    5172772
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2665434