@InProceedings{NomaPardCesa:2008:StMa2D,
               author = "Noma, Alexandre and Pardo, Alvaro and Cesar-Jr, Roberto M.",
          affiliation = "IME-USP, Department of Computer Science, University of Sao Paulo, 
                         Brazil and DIE, Faculty of Engineering and Technologies, Catholic 
                         University of Uruguay and IME-USP, Department of Computer Science, 
                         University of Sao Paulo, Brazil",
                title = "Structural Matching of 2D Electrophoresis Gels using Graph 
                         Models",
            booktitle = "Proceedings...",
                 year = "2008",
               editor = "Jung, Cl{\'a}udio Rosito and Walter, Marcelo",
         organization = "Brazilian Symposium on Computer Graphics and Image Processing, 21. 
                         (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
             keywords = "2D electrophoresis gels, graph matching, structural pattern 
                         recognition, deformation graph, graph models, structural 
                         matching.",
             abstract = "2D electrophoresis is a well known method for protein separation 
                         which is extremely useful in the field of proteomics. Each spot in 
                         the image represents a protein accumulation and the goal is to 
                         perform a differential analysis between pairs of images to study 
                         changes in protein content. It is thus necessary to register two 
                         images by finding spot correspondences. Although it may seem a 
                         simple task, generally, the manual processing of this kind of 
                         images is very cumbersome. The complete task of individual spot 
                         matching and gel registration is a complex and time consuming 
                         process when strong variations between corresponding sets of spots 
                         are expected. Besides, because an one-to-one mapping is expected 
                         between the two images, missing spots there may exist on both 
                         images (i.e. spots without correspondence). In order to solve this 
                         problem, this paper proposes a new distance together with a 
                         correspondence estimation algorithm based on graph matching which 
                         takes into account the structural information between the detected 
                         spots. Each image is represented by a graph and the task is to 
                         find an isomorphism between subgraphs. Successful experimental 
                         results using real data are presented, including a comparative 
                         performance evaluation. .",
  conference-location = "Campo Grande, MS, Brazil",
      conference-year = "12-15 Oct. 2008",
                  doi = "10.1109/SIBGRAPI.2008.14",
                  url = "http://dx.doi.org/10.1109/SIBGRAPI.2008.14",
             language = "en",
                  ibi = "6qtX3pFwXQZG2LgkFdY/UNkhu",
                  url = "http://urlib.net/ibi/6qtX3pFwXQZG2LgkFdY/UNkhu",
           targetfile = "noma-StructuralElectrophoresis.pdf",
        urlaccessdate = "2024, Apr. 27"
}