• DocumentCode
    1580703
  • Title

    Automated segmentation of multiple sclerosis lesions using statistical approach

  • Author

    Sharma, Yamini ; Meghrajani, Yogesh K.

  • Author_Institution
    Dept. of Electron. & Commun., Dharmsinh Desai Univ., Nadiad, India
  • fYear
    2015
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    This paper describes a statistical approach for segmenting multiple sclerosis lesions (tumors) from magnetic resonance imaging (MRI) images. Proposed method detects and segments the areas inside the brain that are affected by tumors. Tumor regions are the areas of higher intensity in comparison to normal tissue. Our automated method gives satisfactory results showing that the proposed method is capable of segmenting multiple sclerosis lesions of different shapes and intensities. In order to show the efficacy of proposed approach, experimental results are compared with the results of other algorithm and also with the results of manual segmentation performed by experts.
  • Keywords
    biomedical MRI; brain; image segmentation; medical image processing; statistical analysis; tumours; MRI image; brain; magnetic resonance imaging; multiple sclerosis lesions automated segmentation; statistical approach; tumors; Gray-scale; Image reconstruction; Image segmentation; Lesions; Magnetic resonance imaging; Multiple sclerosis; MRI image; Multiple sclerosis (MS) lesions; intra - class variance; morphological operations; skull extraction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Innovations in Information, Embedded and Communication Systems (ICIIECS), 2015 International Conference on
  • Conference_Location
    Coimbatore
  • Print_ISBN
    978-1-4799-6817-6
  • Type

    conf

  • DOI
    10.1109/ICIIECS.2015.7193144
  • Filename
    7193144