Title :
Fast automatic myopic deconvolution of angiogram sequences
Author :
Thibon, Louis ; Soulez, Ferreol ; Thiebaut, Eric
Author_Institution :
Centre de Rech. Astrophys. de Lyon, Univ. Lyon 1, Lyon, France
fDate :
April 29 2014-May 2 2014
Abstract :
We present a fast unsupervised myopic deconvolution method dedicated to quasi-real time processing of video sequences such as angiograms. Our method is based on a Bayesian approach of which the tuning parameters are automatically set thanks to the marginalized likelihood of the observed image. We demonstrate the effectiveness of our approach on simulated and empirical images.
Keywords :
Bayes methods; diagnostic radiography; image sequences; maximum likelihood sequence estimation; medical image processing; Bayesian approach; angiogram sequences; empirical images; fast automatic myopic deconvolution method; image simulation; marginalized likelihood; quasi-real time processing; tuning parameters; video sequences; Approximation methods; Deconvolution; Discrete Fourier transforms; Image restoration; Maximum likelihood estimation; Noise; Tuning;
Conference_Titel :
Biomedical Imaging (ISBI), 2014 IEEE 11th International Symposium on
Conference_Location :
Beijing
DOI :
10.1109/ISBI.2014.6868058
