@InProceedings{BejarMira:2016:ReFuCo,
               author = "Bejar, Hans Harley Ccacyahuillca and Miranda, Paulo A. V.",
          affiliation = "IME-USP and IME-USP",
                title = "Relative Fuzzy Connectedness on Directed Graphs and its 
                         Application in a Hybrid Method for Interactive Image 
                         Segmentation",
            booktitle = "Proceedings...",
                 year = "2016",
               editor = "Aliaga, Daniel G. and Davis, Larry S. and Farias, Ricardo C. and 
                         Fernandes, Leandro A. F. and Gibson, Stuart J. and Giraldi, Gilson 
                         A. and Gois, Jo{\~a}o Paulo and Maciel, Anderson and Menotti, 
                         David and Miranda, Paulo A. V. and Musse, Soraia and Namikawa, 
                         Laercio and Pamplona, Mauricio and Papa, Jo{\~a}o Paulo and 
                         Santos, Jefersson dos and Schwartz, William Robson and Thomaz, 
                         Carlos E.",
         organization = "Conference on Graphics, Patterns and Images, 29. (SIBGRAPI)",
            publisher = "Sociedade Brasileira de Computa{\c{c}}{\~a}o",
              address = "Porto Alegre",
             keywords = "Relative fuzzy connectedness, image foresting trans- form, 
                         graph-cut segmentation, graph search algorithms.",
             abstract = "Anatomical structures and tissues are often hard to be segmented 
                         in medical images due to their poorly defined boundaries, i.e., 
                         low contrast in relation to other nearby false boundaries. The 
                         specification of the boundary polarity can help to alleviate part 
                         of this problem. In this work, we discuss how to incorporate this 
                         property in the Relative Fuzzy Connectedness (RFC) framework. We 
                         present a new algorithm, named Oriented Relative Fuzzy 
                         Connectedness (ORFC), in terms of an oriented energy function 
                         subject to the seed constraints, and its application in powerful 
                         hybrid segmentation methods. The hybrid method proposed 
                         ORFC\&Graph Cut preserves the robustness of ORFC respect to the 
                         seed choice, avoiding the shrinking problem of Graph Cut (GC), and 
                         keeps the strong control of the GC in the contour delination of 
                         irregular image boundaries. The proposed methods are evaluated 
                         using medical images of MRI and CT images of the human brain and 
                         thoracic studies.",
  conference-location = "S{\~a}o Jos{\'e} dos Campos, SP, Brazil",
      conference-year = "4-7 Oct. 2016",
             language = "en",
                  ibi = "8JMKD3MGPAW/3MN7RM5",
                  url = "http://urlib.net/ibi/8JMKD3MGPAW/3MN7RM5",
           targetfile = "hans.pdf",
        urlaccessdate = "2024, Apr. 28"
}