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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
Natal, Rio Grande do Norte, Brazil October 09-October 12
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/SIBGRAPI.2005.35XVIII Brazilian Symposium on Computer ...
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Elias Salomão Helou Neto, Universidade Estadual de Campinas
Álvaro Rodolfo De Pierro, Universidade Estadual de Campinas
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.
Citation:
Elias Salomão Helou Neto, Álvaro Rodolfo De Pierro, "On the Effect of Relaxation in the Convergence and Quality of Statistical Image Reconstruction for Emission Tomography Using Block-Iterative Algorithms," sibgrapi, pp.13-20, XVIII Brazilian Symposium on Computer Graphics and Image Processing (SIBGRAPI'05), 2005
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