• DocumentCode
    2807881
  • Title

    Classification of ductal tree structures in galactograms

  • Author

    Skoura, Angeliki ; Barnathan, Michael ; Megalooikonomou, Vasileios

  • Author_Institution
    Comput. Eng. & Inf. Dept., Univ. of Patras, Patras, Greece
  • fYear
    2009
  • fDate
    June 28 2009-July 1 2009
  • Firstpage
    1015
  • Lastpage
    1018
  • Abstract
    The objective of this study is the classification of galactograms, medical images which depict the ductal tree of human breast, in order to provide insight into the relationship between tree topology and radiological findings regarding breast cancer. We present two different descriptors for the classification of the ductal trees; the tree asymmetry index and the maximum common skeleton, both of which quantify the similarity between tree topologies. Experimental results demonstrate the effectiveness of the proposed approach, which reaches a classification accuracy of 83%, and also indicate that our method can potentially aid in early breast cancer diagnosis.
  • Keywords
    cancer; diagnostic radiography; image classification; medical image processing; X-ray galactogram; breast cancer; ductal tree structures; image classification; maximum common skeleton; radiology; tree asymmetry index; tree topology; Biomedical imaging; Breast; Cancer; Classification tree analysis; Dairy products; Data engineering; Ducts; Humans; Medical diagnostic imaging; Tree data structures; Cancer; Image classification; Magnetic resonance imaging; Trees;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Imaging: From Nano to Macro, 2009. ISBI '09. IEEE International Symposium on
  • Conference_Location
    Boston, MA
  • ISSN
    1945-7928
  • Print_ISBN
    978-1-4244-3931-7
  • Electronic_ISBN
    1945-7928
  • Type

    conf

  • DOI
    10.1109/ISBI.2009.5193227
  • Filename
    5193227