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On the Effect of Relaxation in the Convergence and Quality of Statistical Image Reconstruction for Emission Tomography Using Block-Iterative Algorithms

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2 Author(s)
Neto, E.S.H. ; Universidade Estadual de Campinas ; De Pierro, A.R.

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.

Published in:

Computer Graphics and Image Processing, 2005. SIBGRAPI 2005. 18th Brazilian Symposium on

Date of Conference:

09-12 Oct. 2005