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@InProceedings{DesernoSoirOlivArau:2011:ToCoDi,
               author = "Deserno, Thomas M. and Soiron, Michael and Oliveira, Julia E. E. 
                         de and Araujo, Arnaldo de A.",
          affiliation = "Department of Medical Informatics, RWTH Aachen University, Aachen, 
                         Germany and Department of Medical Informatics, RWTH Aachen 
                         University, Aachen, Germany and Department of Computer Science, 
                         Universidade Federal de Minas Gerais Belo Horizonte, MG, Brazil 
                         and Department of Computer Science, Universidade Federal de Minas 
                         Gerais Belo Horizonte, MG, Brazil",
                title = "Towards computer-aided diagnostics of screening mammography using 
                         content-based image retrieval",
            booktitle = "Proceedings...",
                 year = "2011",
               editor = "Lewiner, Thomas and Torres, Ricardo",
         organization = "Conference on Graphics, Patterns and Images, 24. (SIBGRAPI)",
            publisher = "IEEE Computer Society Conference Publishing Services",
              address = "Los Alamitos",
             keywords = "Content-based image retrieval, Computer-aided diagnosis, Principal 
                         component analysis, Support vector machine, Mammography, Breast 
                         lesion, Breast density.",
             abstract = "Screening mammography has been established worldwide for early 
                         detection of breast cancer, one of the main causes of death among 
                         women in occidental countries. In this paper, we aim at moving 
                         towards computer-aided diagnostics of screening mammography. 
                         Tissue and lesion are classified using the methodology of 
                         content-based image retrieval. In addition, we aim at 
                         comprehensive evaluation and have established a large database of 
                         annotated reference images (ground truth), which has been merged 
                         and unified from different sources publicly available to research. 
                         In total, 10,509 mammographic images have been collected from the 
                         different sources. From this, 3,375 images are provided with one 
                         and 430 radiographs with more than one chain code annotations. 
                         This data supports experiments with up to 12 classes, and 233 
                         images per class if a equal distribution is required. Using a 
                         two-dimensional principal component analysis with four eigenvalues 
                         and a support vector machine with Gaussian kernel for feature 
                         extraction and image retrieval, respectively, the precision of 
                         computer-aided diagnosis is above 80%. It therefore may be used as 
                         second opinion in screening mammography.",
  conference-location = "Macei{\'o}",
      conference-year = "Aug. 28 - 31, 2011",
             language = "en",
           targetfile = "Deserno-2011.pdf",
        urlaccessdate = "2019, Dec. 09"
}


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