• DocumentCode
    1647691
  • Title

    Grey-level morphology based segmentation of MRI of the human cortex

  • Author

    Hult, Roger

  • Author_Institution
    Centre for Image Analysis, Uppsala Univ., Sweden
  • fYear
    2001
  • Firstpage
    578
  • Lastpage
    583
  • Abstract
    An algorithm for fully automatic segmentation of the cortex from T1-weighted axial or sagittal MRI data is presented. When analysing 3D MRI images of the brain it is often important to segment the brain from non-brain tissue such as eyes and membranes of the brain. The segmentation algorithm uses a histogram-based method to find accurate threshold values. Four initial masks are created; first two thresholded masks from the original volume, background and brain tissue, then a third mask thresholded from a 3D grey-level eroded version of the volume, brain tissue, and lastly a fourth mask thresholded from a 3D grey-level dilated version of the volume, containing surrounding fat. On the start slice of these masks, binary morphological operations and logical operations are used. Then the rest of the slices are segmented using information from the previous slice combined with the other masks. Information from earlier slices is propagated to keep the segmented volume from leaking into non-brain tissue
  • Keywords
    biomedical MRI; brain; image segmentation; mathematical morphology; medical image processing; statistical analysis; 3D MRI images; T1-weighted data; automatic segmentation; axial data; binary morphological operations; brain tissue; dilated version; eroded version; grey-level morphology; histogram; human cortex; logical operations; sagittal data; slices; thresholded masks; Biomembranes; Brain; Eyes; Histograms; Humans; Image analysis; Image segmentation; Magnetic resonance imaging; Morphology; Neuroscience;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Analysis and Processing, 2001. Proceedings. 11th International Conference on
  • Conference_Location
    Palermo
  • Print_ISBN
    0-7695-1183-X
  • Type

    conf

  • DOI
    10.1109/ICIAP.2001.957072
  • Filename
    957072