• DocumentCode
    2701042
  • Title

    A model based contour searching method

  • Author

    Tang, Yingjie ; He, Lei ; Wang, Xun ; Wee, William G.

  • Author_Institution
    Dept. of Electr. & Comput. Eng. & Comput. Sci., Cincinnati Univ., OH, USA
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    347
  • Lastpage
    354
  • Abstract
    A two-step model based approach to a contour extraction problem is developed to provide a solution to more challenging contour extraction problems of biomedical images. A biomedical contour image is initially processed by a deformable contour method to obtain a first order approximation of the contour. The two-step model includes a linked contour model and a posteriori probability model. Initially, the output contour from the deformable contour method is matched against the linked contour model for both model detection and corresponding landmark contour points identification. Segments obtained from these landmarks are matched for errors. Larger error are then passed on to a regionalized a posteriori probability model for further fine tuning to obtain a final result. Experiments on both MR brain images are most encouraging
  • Keywords
    biomedical MRI; brain; edge detection; medical image processing; modelling; MR brain images; MRI; a posteriori probability model; biomedical contour image; deformable contour method; first order approximation; medical diagnostic imaging; model based contour searching method; regionalized a posteriori probability model; Biomedical computing; Biomedical imaging; Brain; Deformable models; Fourier transforms; Image segmentation; Shape; Spline; Wavelet domain; Wavelet transforms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bio-Informatics and Biomedical Engineering, 2000. Proceedings. IEEE International Symposium on
  • Conference_Location
    Arlington, VA
  • Print_ISBN
    0-7695-0862-6
  • Type

    conf

  • DOI
    10.1109/BIBE.2000.889627
  • Filename
    889627