@InProceedings{BíscaroOlivBergNune:2016:NeDeRe,
               author = "B{\'{\i}}scaro, Helton H and Oliveira, Hellyan and Bergamasco, 
                         Leila C C and Nunes, F{\'a}tima L S",
          affiliation = "Escola de Artes, Ci{\^e}ncias e Humanidades, Universidade de 
                         S{\~a}o Paulo and Escola de Artes, Ci{\^e}ncias e Humanidades, 
                         Universidade de S{\~a}o Paulo and Escola de Artes, Ci{\^e}ncias 
                         e Humanidades, Universidade de S{\~a}o Paulo and Escola de Artes, 
                         Ci{\^e}ncias e Humanidades, Universidade de S{\~a}o Paulo",
                title = "A new descriptor for retrieving 3D objects applied in Congestive 
                         Heart Failure diagnosis",
            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 = "IEEE Computer Society´s Conference Publishing Services",
              address = "Los Alamitos",
             keywords = "Content-Based Image Retrieval (CBIR), Spectral Descriptor, 
                         Three-dimensional Objects, Congestive Heart Failure.",
             abstract = "Content-Based Image Retrieval (CBIR) aims to retrieve similar 
                         graphical objects from large databases based on their contents. 
                         CBIR requires definition of descriptors, algorithms that condense 
                         information from the object in order to represent it usually as a 
                         real number or a vector in Rn. This article presents the Spectral 
                         Descriptor, a new descriptor designed for retrieving 
                         three-dimensional geometric objects applied to aid the diagnosis 
                         of Congestive Heart Failure (CHF). Our descriptor is based on 
                         techniques of compressive sensing and rewrites the coordinates of 
                         3D objects vertices on a basis on which they have a sparse 
                         representation. Tests with surfaces reconstructed from heart MRI 
                         images, specifically from left ventricle, show that the descriptor 
                         has presented a good performance, reaching an average precision of 
                         approximately 85% for CHF and 71% for non-CHF cases, maintaining 
                         high levels of precision. Results also showed that the Spectral 
                         Descriptor can decrease the high dimensionality of features 
                         vectors in CBIR systems.",
  conference-location = "S{\~a}o Jos{\'e} dos Campos, SP, Brazil",
      conference-year = "4-7 Oct. 2016",
                  doi = "10.1109/SIBGRAPI.2016.025",
                  url = "http://dx.doi.org/10.1109/SIBGRAPI.2016.025",
             language = "en",
                  ibi = "8JMKD3MGPAW/3M598D5",
                  url = "http://urlib.net/ibi/8JMKD3MGPAW/3M598D5",
           targetfile = "PID4369075.pdf",
        urlaccessdate = "2024, Apr. 28"
}