• DocumentCode
    1570556
  • Title

    Semi-Automatic 3-D Segmentation of Anatomical Structures of Brain MRI Volumes using Graph Cuts

  • Author

    Doan, H. -N. ; Slabaugh, Greg ; Unal, G. ; Fang, Tao

  • Author_Institution
    Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
  • fYear
    2006
  • Firstpage
    1913
  • Lastpage
    1916
  • Abstract
    We present a semi-automatic segmentation technique of the anatomical structures of the brain: cerebrum, cerebellum, and brain stem. The method uses graph cuts segmentation with an anatomic template for initialization. First, a skull stripping procedure is applied to remove non-brain tissues. Then, the segmentation is done hierarchically by first, extracting first the cerebrum from the brain, and then from the remaining volume the cerebellum and the brain stem are separated. This method is fast and can separate different anatomical structures of the brain in spite of weak boundaries. We describe our approach and present experimental results demonstrating its usefulness.
  • Keywords
    biomedical MRI; brain; image segmentation; medical image processing; neurophysiology; MRI; brain anatomical structure; brain stem; cerebellum; cerebrum; graph cuts; magnetic resonance imaging; semiautomatic 3-D segmentation; Active contours; Anatomical structure; Brain; Computational intelligence; Image segmentation; Intelligent structures; Magnetic resonance imaging; Robustness; Shape; Skull; Biomedical image processing; Image segmentation; Magnetic resonance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 2006 IEEE International Conference on
  • Conference_Location
    Atlanta, GA
  • ISSN
    1522-4880
  • Print_ISBN
    1-4244-0480-0
  • Type

    conf

  • DOI
    10.1109/ICIP.2006.313142
  • Filename
    4106929