• DocumentCode
    2610634
  • Title

    A Nonlinear Variational Model for PET Reconstruction

  • Author

    Yan, Jianhua ; Yu, Jun

  • Author_Institution
    Dept. of Electron. Sci. & Technol., Huazhong Univ. of Sci. & Technol., Wuhan
  • Volume
    4
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    699
  • Lastpage
    702
  • Abstract
    PET image was often influenced by noise. In this paper, we proposed a nonlinear variational model for improving reconstruction of PET images. The use of variational model was due to its effectiveness for reducing noise in 2D images while preserving edges. Our results indicated that the proposed method application to computer-simulated and real PET phantom outperformed the conventional method in terms of both visual quality and quantitative accuracy
  • Keywords
    Poisson distribution; Radon transforms; image denoising; image reconstruction; medical image processing; positron emission tomography; variational techniques; PET image reconstruction; edge preservation; image noise reduction; nonlinear variational; phantom; Application software; Computer applications; Detectors; Electron emission; Event detection; Image reconstruction; Imaging phantoms; Iterative algorithms; Noise reduction; Positron emission tomography;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    1051-4651
  • Print_ISBN
    0-7695-2521-0
  • Type

    conf

  • DOI
    10.1109/ICPR.2006.131
  • Filename
    1699937