%0 Conference Proceedings
%4 sid.inpe.br/banon/2005/06.21.00.46
%2 sid.inpe.br/banon/2005/06.21.00.46.21
%@doi 10.1109/SIBGRAPI.2005.35
%T On the effect of relaxation in the convergence and quality of statistical image reconstruction for emission tomography using block-iterative algorithms
%D 2005
%A Helou Neto, Elias Salomão,
%A De Pierro, Álvaro Rodolfo,
%@affiliation UNICAMP
%E Rodrigues, Maria Andréia Formico,
%E Frery, Alejandro César,
%B Brazilian Symposium on Computer Graphics and Image Processing, 18 (SIBGRAPI)
%C Natal, RN, Brazil
%8 9-12 Oct. 2005
%I IEEE Computer Society
%J Los Alamitos
%S Proceedings
%K emission tomography, iterative algorithms.
%X Relaxation is widely recognized as a useful tool for providing convergence in block-iterative algorithms [1], [2], [6]. In the present article we give new results on the convergence of RAMLA (Row Action Maximum Likelihood Algorithm) [2], filling some important theoretical gaps. Furthermore, because RAMLA and OS-EM (Ordered Subsets - Expectation Maximization) [4] are the algorithms for statistical reconstruction currently being used in commercial emission tomography scanners, we present a comparison between them from the viewpoint of a specific imaging task. Our experiments show the importance of relaxation to improve image quality.
%@language en
%3 heloue_tomography.pdf