@InProceedings{MachadoGeeCamp:2002:SuSeBa,
               author = "Machado, Alexei M. C. and Gee, James C. and Campos, Mario F. M.",
                title = "Substructural segmentation based on regional shape differences",
            booktitle = "Proceedings...",
                 year = "2002",
               editor = "Gon{\c{c}}alves, Luiz Marcos Garcia and Musse, Soraia Raupp and 
                         Comba, Jo{\~a}o Luiz Dihl and Giraldi, Gilson and Dreux, 
                         Marcelo",
         organization = "Brazilian Symposium on Computer Graphics and Image Processing, 15. 
                         (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
                 note = "The conference was held in Fortaleza, CE, Brazil, from October 7 
                         to 10.",
             abstract = "This article presents a method for the segmentation of 
                         substructures based on exploratory factor analysis. In this 
                         approach, a high-dimensional set of shape-related variables is 
                         examined with the purpose of finding clusters with strong 
                         correlation. This clustering can potentially identify regions that 
                         have anatomic significance and thus lend insight to morphometric 
                         investigations. The information about regional shape is extracted 
                         by registering a reference image to a set of test images.Based on 
                         the displacement fields obtained form image registration,the 
                         amount of pointwise volume enlargement or reduction is computed 
                         and statistically analyzed with the purpose of extracting a 
                         reduced set of common factors. The effectiveness and robustness of 
                         the method is demonstrated in a study of the human corpus callosum 
                         anatomy,based on a sample of 84 right-handed normal controls. The 
                         method is able to partition the structure into regions of interest 
                         that present correlated shape variation. The confidence of results 
                         is evaluated by analyzing the statistical fit of the model.",
  conference-location = "Fortaleza, CE, Brazil",
      conference-year = "10-10 Oct. 2002",
                  doi = "10.1109/SIBGRA.2002.1167117",
                  url = "http://dx.doi.org/10.1109/SIBGRA.2002.1167117",
             language = "en",
         organisation = "SBC - Brazilian Computer Society",
                  ibi = "6qtX3pFwXQZeBBx/vRkJ3",
                  url = "http://urlib.net/ibi/6qtX3pFwXQZeBBx/vRkJ3",
           targetfile = "14.pdf",
        urlaccessdate = "2024, Apr. 30"
}