Automated analysis of mammographic densities and breast carcinoma risk.

  title={Automated analysis of mammographic densities and breast carcinoma risk.},
  author={J. W. Byng and Martin Joel Yaffe and Gina A. Lockwood and Lewis E. Little and David Tritchler and Norman F. Boyd},
  volume={80 1},
BACKGROUND There is considerable evidence that one of the strongest risk factors for breast carcinoma can be assessed from the mammographic appearance of the breast. However, the magnitude of the risk factor and the reliability of the prediction depend on the method of classification. Subjective classification requires specialized observer training and suffers from inter- and intraobserver variability. Furthermore, the categoric scales make it difficult to distinguish small differences in… CONTINUE READING

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