• DocumentCode
    2477356
  • Title

    Actual Midline Estimation from Brain CT Scan Using Multiple Regions Shape Matching

  • Author

    Wenan Chen ; Najarian, K. ; Ward, K.

  • Author_Institution
    Dept. of Comput. Sci. & VCURES, Virginia Commonwealth Univ., Richmond, VA, USA
  • fYear
    2010
  • fDate
    23-26 Aug. 2010
  • Firstpage
    2552
  • Lastpage
    2555
  • Abstract
    Computer assisted medical image processing can extract vital information that may be elusive to human eyes. In this paper, an algorithm is proposed to automatically estimate the position of the actual midline from the brain CT scans using multiple regions shape matching. The method matches feature points identified from a set of ventricle templates, extracted from MRI, with the corresponding feature points in the segmented ventricles from CT images. Then based on the matched feature points, the position of the actual midline is estimated. The proposed multiple regions shape matching algorithm addresses the deformation problem arising from the intrinsic multiple regions nature of the brain ventricles. Experiments on the CT scans from patients with traumatic brain injuries (TBI) show promising results, particularly the proposed algorithm proves to be quite robust.
  • Keywords
    biomedical MRI; brain; computerised tomography; estimation theory; feature extraction; image matching; image segmentation; medical image processing; CT image ventricle segmentation; MRI; TBI; brain CT scan; computer assisted medical image processing; deformation problem; feature point matching; midline position estimation; multiple region shape matching algorithm; position estimation; traumatic brain injuries; ventricle templates; Biomedical imaging; Computed tomography; Context; Estimation; Image segmentation; Pathology; Shape; actual midline; brain ventricles; shape matching;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition (ICPR), 2010 20th International Conference on
  • Conference_Location
    Istanbul
  • ISSN
    1051-4651
  • Print_ISBN
    978-1-4244-7542-1
  • Type

    conf

  • DOI
    10.1109/ICPR.2010.625
  • Filename
    5595786