Applying modular classifiers to mammographic mass classification

@article{Shah2004ApplyingMC,
  title={Applying modular classifiers to mammographic mass classification},
  author={V. P. Shah and L. M. Bruce and N. H. Younan},
  journal={The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society},
  year={2004},
  volume={1},
  pages={1585-1588}
}
Classification is the last step in the computer aided diagnosis (CAD) system for determining whether a breast mass segmented from a digital mammogram is malignant or benign. Hence it is important to improve sensitivity at this stage. This work investigates the use of modular classifier (MoC) schemes, namely bagging and adaboost algorithms, for automated classification of mammographic masses. CAD systems containing a MoC are compared to CAD systems that contain traditional classifiers (TrC), for… CONTINUE READING

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