• DocumentCode
    3093664
  • Title

    Brain MR Image Tumor Segmentation with Ventricular Deformation

  • Author

    Xiao, Kai ; Hassanien, Aboul Ella ; Sun, Yan ; Ng, Edwin Kit Keong

  • Author_Institution
    Sch. of Software, Shanghai Jiao Tong Univ., Shanghai, China
  • fYear
    2011
  • fDate
    12-15 Aug. 2011
  • Firstpage
    297
  • Lastpage
    302
  • Abstract
    This paper addresses the issue of the weak association between brain MRI intensity value and anatomical meaning of MR image pixels. By investigating the deformation on brain lateral ventricles and compression from tumor, the correlation between them is quantified and utilized. With the proposed feature extraction component, lateral ventricular deformation is transformed into an additional feature for brain tumor segmentation. Some comparative experiments using both supervised and unsupervised pattern recognition segmentation methods show the improved tumor segmentation accuracy in some image cases.
  • Keywords
    biomedical MRI; brain; feature extraction; image resolution; image segmentation; medical image processing; tumours; MR image pixels; anatomical meaning; brain MR image tumor segmentation; brain MRI intensity value; brain lateral ventricles deformation; brain tumor segmentation; feature extraction component; lateral ventricular deformation; supervised pattern recognition segmentation method; unsupervised pattern recognition segmentation method; Biomedical imaging; Deformable models; Feature extraction; Image segmentation; Magnetic resonance imaging; Shape; Tumors; MR image; MRI; brain tumor; deformation; feature; lateral ventricles; medical image analysis; segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image and Graphics (ICIG), 2011 Sixth International Conference on
  • Conference_Location
    Hefei, Anhui
  • Print_ISBN
    978-1-4577-1560-0
  • Electronic_ISBN
    978-0-7695-4541-7
  • Type

    conf

  • DOI
    10.1109/ICIG.2011.141
  • Filename
    6005572