• DocumentCode
    1955260
  • Title

    Automatic segmentation and labeling of human brain tissue from MR images

  • Author

    Mokbel, H.A. ; Morsy, M.El-S. ; Abou-Chadi, F.E.Z.

  • Author_Institution
    Fac. of Eng., Mansoura Univ., Egypt
  • fYear
    2000
  • fDate
    2000
  • Abstract
    This work presents a technique for automatic tissue labeling of 2-D magnetic resonance (MR) images of the human brain. This technique consists of two components: an unsupervised clustering algorithm and a knowledge-based technique. The knowledge-based technique contains information on the cluster distribution in feature space and tissue models. This approach also provides a first step toward classification of normal and abnormal images
  • Keywords
    biological tissues; biomedical MRI; brain; image classification; image segmentation; knowledge based systems; medical image processing; pattern clustering; unsupervised learning; 2-D magnetic resonance images; MR images; abnormal images; automatic segmentation; classification; cluster distribution; feature space; human brain tissue; knowledge-based technique; labeling; normal images; tissue models; unsupervised clustering algorithm; Biomedical imaging; Brain; Clustering algorithms; Fuzzy sets; Humans; Image segmentation; Labeling; Magnetic resonance; Magnetic resonance imaging; Skull;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Radio Science Conference, 2000. 17th NRSC '2000. Seventeenth National
  • Conference_Location
    Minufiya
  • Print_ISBN
    977-5031-64-8
  • Type

    conf

  • DOI
    10.1109/NRSC.2000.838979
  • Filename
    838979