• DocumentCode
    3473802
  • Title

    Efficient textural model-based mammogram enhancement

  • Author

    Haindl, Michal ; Remes, Vaclav

  • Author_Institution
    Fac. of Inf. Technol., CTU in Prague, Prague, Czech Republic
  • fYear
    2013
  • fDate
    20-22 June 2013
  • Firstpage
    522
  • Lastpage
    523
  • Abstract
    An efficient method for X-ray digital mammogram multi-view enhancement based on the underlying two-dimensional adaptive causal autoregressive texture model is presented. The method locally predicts breast tissue texture from multi-view mammograms and enhances breast tissue abnormalities, such as the sign of a developing cancer, using the estimated model prediction error. The mammo-gram enhancement is based on the cross-prediction error of mutually registered left and right breasts mammograms or on the single-view model prediction error if both breasts´ mammograms are not available.
  • Keywords
    cancer; image enhancement; image registration; image texture; mammography; medical image processing; 2D adaptive causal autoregressive texture model; X-ray digital mammogram; breast tissue abnormalities; breast tissue texture; cross prediction error; developing breast cancer; estimated model prediction error; mammogram multiview enhancement; multiview mammograms; mutually registered breast mammograms; single view model prediction error; textural model based mammogram enhancement; Adaptation models; Breast cancer; Computers; Predictive models; Solid modeling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer-Based Medical Systems (CBMS), 2013 IEEE 26th International Symposium on
  • Conference_Location
    Porto
  • Type

    conf

  • DOI
    10.1109/CBMS.2013.6627859
  • Filename
    6627859