• DocumentCode
    2836215
  • Title

    Skull stripping of MRI brain images using mathematical morphology

  • Author

    Roslan, Rosniza ; Jamil, Nursuriati ; Mahmud, Rozi

  • Author_Institution
    Fac. of Comput. & Math. Sci., MARA Univ. of Technol., Shah Alam, Malaysia
  • fYear
    2010
  • fDate
    Nov. 30 2010-Dec. 2 2010
  • Firstpage
    26
  • Lastpage
    31
  • Abstract
    Skull stripping is a major phase in MRI brain imaging applications and it refers to the removal of its non-cerebral tissues. The main problem in skull-stripping is the segmentation of the non-cerebral and the intracranial tissues due to their homogeneity intensities. As morphology requires prior binarization of the image, this paper proposed mathematical morphology segmentation using double and Otsu´s thresholding. The purpose is to identify robust threshold values to remove the non-cerebral tissue from MRI brain images. Ninety collected samples of T1-weighted, T2-weighted and FLAIR MRI brain images are used in the experiments. The results showed promising use of double threholding as a robust threshold value in handling intensity inhomogeneities compared to Otsu´s thresholding.
  • Keywords
    biological tissues; biomedical MRI; brain; image segmentation; mathematical morphology; medical image processing; FLAIR MRI brain images; MRI brain images; Otsu thresholding; T1-weighted images; T2-weighted images; double thresholding; homogeneity intensities; image segmentation; mathematical morphology; noncerebral tissues; skull stripping; Brain; Image segmentation; Image sequences; Magnetic resonance imaging; Morphology; Robustness; Skull; MRI; Mathematical Morphology; Skull Stripping; Thresholding;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Engineering and Sciences (IECBES), 2010 IEEE EMBS Conference on
  • Conference_Location
    Kuala Lumpur
  • Print_ISBN
    978-1-4244-7599-5
  • Type

    conf

  • DOI
    10.1109/IECBES.2010.5742193
  • Filename
    5742193