• DocumentCode
    2345509
  • Title

    Unsupervised Bayesian segmentation with bootstrap sampling application to eye fundus image coding

  • Author

    Dutendas, D. ; Moreau, L. ; Ghorbel, F. ; Allioux, P.M.

  • Author_Institution
    Groupe Recherche Image & Formes, ENIC-INT, Villeneuve d´´Ascq, France
  • Volume
    4
  • fYear
    1994
  • fDate
    30 Oct-5 Nov 1994
  • Firstpage
    1794
  • Abstract
    The authors propose a scheme of retina images coding. First of all, they describe the basis and the algorithm of the unsupervised Bayesian segmentation with the principle of bootstrap sampling. The second part deals with the integration of this quantification within a retinal images coding scheme including an orthogonal transform and variable length coding
  • Keywords
    Bayes methods; bootstrapping; eye; image coding; image sampling; image segmentation; laser applications in medicine; medical image processing; bootstrap sampling; eye fundus image coding; medical diagnostic images; ocular images; orthogonal transform; retinal images coding scheme; unsupervised Bayesian segmentation algorithm; variable length coding; Angiography; Bayesian methods; Elbow; Encoding; Image coding; Image sampling; Image segmentation; Probability density function; Retina; Veins;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Nuclear Science Symposium and Medical Imaging Conference, 1994., 1994 IEEE Conference Record
  • Conference_Location
    Norfolk, VA
  • Print_ISBN
    0-7803-2544-3
  • Type

    conf

  • DOI
    10.1109/NSSMIC.1994.474716
  • Filename
    474716