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@InProceedings{HelouNetoPier:2005:EfReCo,
               author = "Helou Neto, Elias Salom{\~a}o and De Pierro, {\'A}lvaro 
                         Rodolfo",
          affiliation = "UNICAMP",
                title = "On the effect of relaxation in the convergence and quality of 
                         statistical image reconstruction for emission tomography using 
                         block-iterative algorithms",
            booktitle = "Proceedings...",
                 year = "2005",
               editor = "Rodrigues, Maria Andr{\'e}ia Formico and Frery, Alejandro 
                         C{\'e}sar",
         organization = "Brazilian Symposium on Computer Graphics and Image Processing, 18. 
                         (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
             keywords = "emission tomography, iterative algorithms.",
             abstract = "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.",
  conference-location = "Natal",
      conference-year = "9-12 Oct. 2005",
             language = "en",
           targetfile = "heloue_tomography.pdf",
        urlaccessdate = "2020, Dec. 04"
}


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