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
fDate :
30 Oct-5 Nov 1994
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;
Conference_Titel :
Nuclear Science Symposium and Medical Imaging Conference, 1994., 1994 IEEE Conference Record
Conference_Location :
Norfolk, VA
Print_ISBN :
0-7803-2544-3
DOI :
10.1109/NSSMIC.1994.474716
