author = "Mansilla, Lucy A. C. and Cappabianco, F{\'a}bio A. M. and 
                         Miranda, Paulo A. V.",
          affiliation = "Department of Computer Science, University of S{\~a}o Paulo (USP) 
                         and Instituto de Ci{\^e}ncia e Tecnologia, Universidade Federal 
                         de S{\~a}o Paulo and Department of Computer Science, University 
                         of S{\~a}o Paulo (USP)",
                title = "Image Segmentation by Image Foresting Transform with Non-smooth 
                         Connectivity Functions",
            booktitle = "Proceedings...",
                 year = "2013",
               editor = "Boyer, Kim and Hirata, Nina and Nedel, Luciana and Silva, 
         organization = "Conference on Graphics, Patterns and Images, 26. (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
             keywords = "graph search algorithms, image foresting transform, non-smooth 
                         connectivity functions.",
             abstract = "In the framework of the Image Foresting Transform (IFT), there is 
                         a class of connectivity functions that were vaguely explored, 
                         which corresponds to the non-smooth connectivity functions (NSCF). 
                         These functions are more adaptive to cope with the problems of 
                         field inhomogeneity, which are common in MR images of 3 Tesla. In 
                         this work, we investigate the NSCF from the standpoint of 
                         theoretical and experimental aspects. We formally classify several 
                         non-smooth functions according to a proposed diagram 
                         representation. Then, we investigate some theoretical properties 
                         for some specific regions of the diagram. Our analysis reveals 
                         that many NSCFs are, in fact, the result of a sequence of 
                         optimizations, each of them involving a maximal set of elements, 
                         in a well-structured way. Our experimental results indicate that 
                         substantial improvements can be obtained by NSCFs in the 3D 
                         segmentation of MR images of 3 Tesla, when compared to smooth 
                         connectivity functions.",
  conference-location = "Arequipa, Peru",
      conference-year = "Aug. 5-8, 2013",
             language = "en",
           targetfile = "114732_new.pdf",
        urlaccessdate = "2020, Dec. 05"