• DocumentCode
    2321567
  • Title

    A Set-based Hybrid Approach (SHA) for MRI Segmentation

  • Author

    Liu, Jiang ; Leong, Tze-Yun ; Chee, Kin Ban ; Tan, Boon Pin ; Shuter, Borys ; Wang, Shih-Chang

  • Author_Institution
    Dept. of Comput. Sci., Nat. Univ. of Singapore
  • fYear
    2006
  • fDate
    5-8 Dec. 2006
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This paper describes a new hybrid approach set-based hybrid approach (SHA) for magnetic resonance (MR) image segmentation by integrating two existing techniques, region-grow and threshold level set. To evaluate the proposed approach in performing real world image segmentation task, instead of using well-taken MR-images, we use real-life images collected in a hospital. Comparison of the performance between the two individual techniques and the new hybrid technique demonstrates the effectiveness of the latter
  • Keywords
    biomedical MRI; image segmentation; medical image processing; set theory; magnetic resonance image segmentation; region growth; set-based hybrid approach; threshold level set; Biomedical imaging; Computer science; Differential equations; Image edge detection; Image segmentation; Level set; Magnetic resonance; Magnetic resonance imaging; Medical diagnostic imaging; Radiology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control, Automation, Robotics and Vision, 2006. ICARCV '06. 9th International Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    1-4244-0341-3
  • Electronic_ISBN
    1-4214-042-1
  • Type

    conf

  • DOI
    10.1109/ICARCV.2006.345358
  • Filename
    4150342