• DocumentCode
    119829
  • Title

    Image segmentation using active contour models and partial differential equations

  • Author

    Livada, Caslav ; Leventic, Hrvoje ; Galic, Irena

  • Author_Institution
    Fac. of Electr. Eng. in Osijek, Univ. of Osijek, Osijek, Croatia
  • fYear
    2014
  • fDate
    10-12 Sept. 2014
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    This article displays benefits of image segmentation for purpose of 3D reconstruction. Medical images and in this case CT slices are being reconstructed in 3D space for better medical investigation. It is relatively hard to use raw images for 3D reconstruction, so certain areas are being singled out using active contour models. Partial Differential Equations (PDEs), as non-linear diffusion, are used for image denoising because CT images have large gradiental areas that need to be evened out.
  • Keywords
    computerised tomography; image denoising; image reconstruction; image segmentation; medical image processing; partial differential equations; 3D reconstruction; CT slices; PDE; active contour models; image denoising; image segmentation; medical image reconstruction; nonlinear diffusion; partial differential equations; Active contours; Equations; Heart; Image edge detection; Image segmentation; Mathematical model; Three-dimensional displays; 3D reconstruction; Active Contours; MRI; Non linear-diffusion; PDEs;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    ELMAR (ELMAR), 2014 56th International Symposium
  • Conference_Location
    Zadar
  • Type

    conf

  • DOI
    10.1109/ELMAR.2014.6923348
  • Filename
    6923348