Feature selection for computerized mass detection in digitized mammograms by using a genetic algorithm.

@article{Zheng1999FeatureSF,
  title={Feature selection for computerized mass detection in digitized mammograms by using a genetic algorithm.},
  author={Bin Zheng and Y. H. Chang and X. H. Wang and Walter F. Good and David Gur},
  journal={Academic radiology},
  year={1999},
  volume={6 6},
  pages={327-32}
}
RATIONALE AND OBJECTIVES To investigate optimization of feature selection for computerized mass detection in digitized mammograms, and to compare the effectiveness of a genetic algorithm (GA) in such optimization with that of an "exhaustive" search of all feature permutations. MATERIALS AND METHODS A Bayesian belief network (BBN) was used to classify positive and negative regions for masses depicted in digitized mammograms; 20 features were computed for each of 592 positive and 3,790 negative… CONTINUE READING