• DocumentCode
    1652138
  • Title

    Detections of Microcalcification Clusters Using Multiple Mammographic Views

  • Author

    Li, Ma ; Shan Yajing

  • Author_Institution
    Sch. of Autom., Hangzhu Dianzi Univ., Hangzhou
  • fYear
    2008
  • Firstpage
    361
  • Lastpage
    365
  • Abstract
    To reduce the false positive hits, a new method for the computer aided detection of microcalcification clusters is proposed in the paper by joint analysis of two views of the same breast. The novelty of the scheme includes a consequent two steps of matching processes: spatial and feature matching. The former links a suspicious cluster located on the MLO view with a corresponding location on the CC view using their spatial information to form a paired cluster, and then in the latter stage, each cluster candidates are characterized by its single-view features such as size, shape and intensity. Finally a similarity function is calculated between the pair to determine if they were true microcalcification clusters. The experiments show that the proposed method has advantages of lower FP rate compared to the one on a single view.
  • Keywords
    biological organs; feature extraction; image matching; image segmentation; mammography; medical image processing; CC view; MLO view; breast; computer aided detection; feature matching; mammographic view; microcalcification cluster detection; spatial matching; Automation; Breast cancer; Cancer detection; Computer vision; Detection algorithms; Feature extraction; Fractals; Multi-layer neural network; Neural networks; Shape;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedical Engineering, 2008. ICBBE 2008. The 2nd International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-1747-6
  • Electronic_ISBN
    978-1-4244-1748-3
  • Type

    conf

  • DOI
    10.1109/ICBBE.2008.92
  • Filename
    4534972