• DocumentCode
    3250016
  • Title

    A novel method of CT brain images segmentation

  • Author

    Zang, Xiaojun ; Wang, Yongtian ; Yang, Jian ; Liu, Yue

  • Author_Institution
    Sch. of Optoelectron., Beijing Inst. of Technol., Beijing, China
  • fYear
    2010
  • fDate
    10-13 June 2010
  • Firstpage
    109
  • Lastpage
    112
  • Abstract
    In this paper, an algorithm is developed for anatomical structures segmentation based on CT head images. The segmented structure can be used for image guide surgery navigations. In our method, intensity rescaling, the threshold algorithm, region growing method, fast-marching method (FMM) and mathematical morphology are combined and used systematically. Due to the low contrast of the CT images, intensity rescaling is applied to the images to enhance the contrast. Threshold algorithm is used to extract the intracranial area from the enhanced images. Then, FMM is adopted to segment the intracranial images of brain matter and cerebrospinal fluid (CSF). Mathematical morphology is used to correct the pre-calculated images and obtain accurate brain matter and CSF segmentations. The system has been tested with a number of real CT head images and has achieved some promising results.
  • Keywords
    brain; computerised tomography; feature extraction; image enhancement; image segmentation; mathematical morphology; medical image processing; CT head images; brain image segmentation; brain matter; cerebrospinal fluid; computerised tomography; contrast enhancement; fast-marching method; image guide surgery navigations; intensity rescaling; intracranial area extraction; mathematical morphology; region growing method; threshold algorithm; Anatomical structure; Biomedical imaging; Brain; Computed tomography; Flowcharts; Head; Histograms; Image analysis; Image segmentation; Morphology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Medical Image Analysis and Clinical Applications (MIACA), 2010 International Conference on
  • Conference_Location
    Guangdong
  • Print_ISBN
    978-1-4244-8011-1
  • Type

    conf

  • DOI
    10.1109/MIACA.2010.5528508
  • Filename
    5528508