• DocumentCode
    2358432
  • Title

    Automatic lesion/tumor detection using intelligent mesh-based active contour

  • Author

    Yin, Lijun ; Deshpande, Sandeep ; Chang, Ja Kwei

  • Author_Institution
    Dept. of Comput. Sci., State Univ. of New York, Binghamton, NY, USA
  • fYear
    2003
  • fDate
    3-5 Nov. 2003
  • Firstpage
    390
  • Lastpage
    397
  • Abstract
    Automatic detection of the lesion/tumor region is always of interest in medical imaging system. We address this issue in this paper for improving the accuracy and robustness as compared to the conventional methods. Active contour has been commonly used for the detection of irregular shape of region, however, it suffers the problem of the false attraction given the noisy image, and requires the correct estimation of the initial location of the object to be detected. In this paper, we present a novel method for robustly locating the object area by using a so-called intelligent mesh. With the accurate location and shape approximation in the initial stage, the object of interest is correctly detected by using a mesh-based active contour model. The correctness and robustness of the proposed algorithm are demonstrated on extracting the lesion/tumor regions of CT and Mammography images as an intensive test.
  • Keywords
    mammography; medical computing; medical image processing; mesh generation; tumours; CT; CT images; algorithm; automatic lesion/tumor detection; intelligent mesh; intelligent mesh-based active contour; lesion/tumor detection; mammography; mammography images; medical imaging; mesh-based active contour; Active contours; Active noise reduction; Biomedical imaging; Lesions; Neoplasms; Noise shaping; Object detection; Robustness; Shape; Tumors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Tools with Artificial Intelligence, 2003. Proceedings. 15th IEEE International Conference on
  • ISSN
    1082-3409
  • Print_ISBN
    0-7695-2038-3
  • Type

    conf

  • DOI
    10.1109/TAI.2003.1250216
  • Filename
    1250216