Identity statement area
Reference TypeConference Paper (Conference Proceedings)
Last Update2005: (UTC) administrator
Metadata Last Update2020: (UTC) administrator
Citation KeyHelouNetoPier:2005:EfReCo
TitleOn the effect of relaxation in the convergence and quality of statistical image reconstruction for emission tomography using block-iterative algorithms
Access Date2021, Nov. 27
Number of Files1
Size662 KiB
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Author1 Helou Neto, Elias Salomão
2 De Pierro, Álvaro Rodolfo
Affiliation1 UNICAMP
EditorRodrigues, Maria Andréia Formico
Frery, Alejandro César
Conference NameBrazilian Symposium on Computer Graphics and Image Processing, 18 (SIBGRAPI)
Conference LocationNatal
Date9-12 Oct. 2005
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2005-06-21 00:46:22 :: eshneto -> banon ::
2005-06-22 21:12:25 :: banon -> eshneto ::
2008-07-17 14:10:58 :: eshneto -> banon ::
2008-08-26 15:17:00 :: banon -> administrator ::
2009-08-13 20:37:41 :: administrator -> banon ::
2010-08-28 20:01:16 :: banon -> administrator ::
2020-02-19 03:19:05 :: administrator -> :: 2005
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Is the master or a copy?is the master
Content Stagecompleted
Content TypeExternal Contribution
Keywordsemission tomography
iterative algorithms
AbstractRelaxation 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.
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User Groupeshneto
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