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@InProceedings{SalvadeoMascLeva:2012:CoFiCT,
               author = "Salvadeo, Denis Henrique Pinheiro and Mascarenhas, Nelson Delfino 
                         d'{\'A}vila and Levada, Alexandre Lu{\'{\i}}s Magalh{\~a}es",
          affiliation = "{Federal University of S{\~a}o Carlos (UFSCar)} and {Federal 
                         University of S{\~a}o Carlos (UFSCar)} and {Federal University of 
                         S{\~a}o Carlos (UFSCar)}",
                title = "Contextual filtering of CT images using Markovian Wiener filters 
                         with a Non Local Means approach for statistical estimation",
            booktitle = "Proceedings...",
                 year = "2012",
               editor = "Freitas, Carla Maria Dal Sasso and Sarkar, Sudeep and Scopigno, 
                         Roberto and Silva, Luciano",
         organization = "Conference on Graphics, Patterns and Images, 25. (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
             keywords = "Wiener filter, Fisher Information, Markov Random Fields, Non Local 
                         Means approach, image denoising, Computed Tomography.",
             abstract = "Recently, investigations on medical imaging have been indicating a 
                         strong correlation between cases of cancers and the increasing 
                         number of Computed Tomography (CT) exams, mainly due to high 
                         radiation doses to which patients are exposed during the data 
                         acquisition process. Thus, there is a need to reduce the radiation 
                         doses whereas still keeping satisfactory quality images for 
                         diagnosis. In this paper, we propose to filter noise in CT images 
                         using contextual versions of Wiener Filter such as Generalized 
                         Wiener Filter (GWF) and Non Local Means approach for parameter 
                         estimation. Experiments show that the proposed methods are 
                         promising, since they provide good results with no significant 
                         increase in the computational cost.",
  conference-location = "Ouro Preto",
      conference-year = "Aug. 22-25, 2012",
             language = "en",
           targetfile = "101966.pdf",
        urlaccessdate = "2021, Jan. 28"
}


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