Segmentation of suspicious densities in digital mammograms.

@article{Brake2001SegmentationOS,
  title={Segmentation of suspicious densities in digital mammograms.},
  author={Guido te Brake and Nico Karssemeijer},
  journal={Medical physics},
  year={2001},
  volume={28 2},
  pages={259-66}
}
State-of-the-art algorithms for detection of masses in mammograms are very sensitive but they also detect many normal regions with slightly suspicious features. Based on segmentations of detected regions, shape and intensity features can be computed that discriminate between normal and abnormal regions. These features can be used to discard false positive detections and hence improve the specificity of the detection method. In this work two different methods to segment suspect regions were… CONTINUE READING

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