• DocumentCode
    2116414
  • Title

    Classification trees for fast segmentation of DTI brain fiber tracts

  • Author

    Zimmerman-Moreno, Gali ; Mayer, Arnaldo ; Greenspan, Hayit

  • Author_Institution
    Dept. of Biomed. Eng., Tel-Aviv Univ., Tel-Aviv
  • fYear
    2008
  • fDate
    23-28 June 2008
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    A method is proposed for modeling and classification of White Matter fiber tracts in the brain. The presented scheme uses classification trees in conjunction with spatial representation of the individual fibers, in order to capture the characteristic behavior of fibers belonging to a specific anatomical structure. The method is characterized by high classification speed, under 3 seconds for all the fibers in a typical DTI of a brain. The model has the ability to represent complex geometric structures and has an intuitive interpretation. Encouraging results are demonstrated for tract classification on real data from ten different subjects.
  • Keywords
    biomedical MRI; brain; image classification; image segmentation; medical image processing; DTI brain fiber tract segmentation; MRI brain; classification trees; complex geometric structures; diffusion tensor imaging; spatial representation; white matter; Anatomical structure; Biomedical engineering; Brain modeling; Classification tree analysis; Data mining; Diffusion tensor imaging; Image reconstruction; Magnetic resonance imaging; Solid modeling; Tensile stress;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition Workshops, 2008. CVPRW '08. IEEE Computer Society Conference on
  • Conference_Location
    Anchorage, AK
  • ISSN
    2160-7508
  • Print_ISBN
    978-1-4244-2339-2
  • Electronic_ISBN
    2160-7508
  • Type

    conf

  • DOI
    10.1109/CVPRW.2008.4562998
  • Filename
    4562998