• DocumentCode
    3399652
  • Title

    A Mixed Model Based on Watershed and Active Contour Algorithms for Brain Tumor Segmentation

  • Author

    Bhat, Subramanya ; Kunte, Sanjeev R

  • Author_Institution
    Electron. & Commun. Eng. Dept., Canara Eng. Coll., Mangalore, India
  • fYear
    2010
  • fDate
    16-17 Oct. 2010
  • Firstpage
    398
  • Lastpage
    400
  • Abstract
    Segmentation of anatomical regions is the fundamental problem in medical image analysis. The watershed algorithm is used for the segmentation of anatomical regions and it is computationally simple. The active contour algorithm is used to extract the tumor region in the segmented image, but it suffers from computational complexity and it is insensitive to noise. The proposed method combines watershed algorithm with active contour algorithm to reduce the computational complexity and to improve the insensitiveness to noise. The real brain MR image is first segmented using watershed segmentation and then edges produced will be the initial contour of active contour algorithm. The proposed method is superior in terms of capture range, concave tumor region extraction, segmentation accuracy and sensitivity to noise.
  • Keywords
    biomedical MRI; brain; computational complexity; concave programming; image segmentation; medical image processing; tumours; active contour algorithms; anatomical regions; brain MR image; brain tumor segmentation; computational complexity; concave tumor region extraction; medical image analysis; noise sensitivity; segmentation accuracy; segmented image; watershed algorithm; watershed segmentation; Accuracy; Active contours; Algorithm design and analysis; Biomedical imaging; Image segmentation; Noise; Tumors; active contour; brain tumor; watershed;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advances in Recent Technologies in Communication and Computing (ARTCom), 2010 International Conference on
  • Conference_Location
    Kottayam
  • Print_ISBN
    978-1-4244-8093-7
  • Electronic_ISBN
    978-0-7695-4201-0
  • Type

    conf

  • DOI
    10.1109/ARTCom.2010.13
  • Filename
    5655581