• DocumentCode
    2133281
  • Title

    Automatic segmentation framework for primary tumors from brain MRIs using morphological filtering techniques

  • Author

    Ananda, Resmi S. ; Thomas, Tessamma

  • Author_Institution
    Dept. of Electron. Eng., Coll. of Eng. Perumon, Kollam, India
  • fYear
    2012
  • fDate
    16-18 Oct. 2012
  • Firstpage
    238
  • Lastpage
    242
  • Abstract
    This paper describes a novel framework for automatic segmentation of primary tumors and its boundary from brain MRIs using morphological filtering techniques. This method uses T2 weighted and T1 FLAIR images. This approach is very simple, more accurate and less time consuming than existing methods. This method is tested by fifty patients of different tumor types, shapes, image intensities, sizes and produced better results. The results were validated with ground truth images by the radiologist. Segmentation of the tumor and boundary detection is important because it can be used for surgical planning, treatment planning, textural analysis, 3-Dimensional modeling and volumetric analysis.
  • Keywords
    biomedical MRI; brain; image segmentation; image texture; medical image processing; neurophysiology; surgery; tumours; 3-dimensional modeling; T1 FLAIR images; T2 weighted images; automatic segmentation framework; boundary detection; brain MRI; image intensities; morphological filtering techniques; primary tumors; surgical planning; textural analysis; treatment planning; volumetric analysis; Brain MRI; Dilation; Erosion; Morphological filtering; Primary tumor; Segmentation; Tumor boundary;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Engineering and Informatics (BMEI), 2012 5th International Conference on
  • Conference_Location
    Chongqing
  • Print_ISBN
    978-1-4673-1183-0
  • Type

    conf

  • DOI
    10.1109/BMEI.2012.6512995
  • Filename
    6512995