A new mass classification system derived from multiple features and a trained MLP model

@inproceedings{Tan2014ANM,
  title={A new mass classification system derived from multiple features and a trained MLP model},
  author={Maxine Tan and Jiantao Pu and Bin Zheng},
  booktitle={Medical Imaging: Computer-Aided Diagnosis},
  year={2014}
}
High false-positive recall rate is an important clinical issue that reduces efficacy of screening mammography. Aiming to help improve accuracy of classification between the benign and malignant breast masses and then reduce false-positive recalls, we developed and tested a new computer-aided diagnosis (CAD) scheme for mass classification using a database including 600 verified mass regions. The mass regions were segmented from regions of interest (ROIs) with a fixed size of 512 512× pixels. The… CONTINUE READING

References

Publications referenced by this paper.
SHOWING 1-10 OF 32 REFERENCES

An automatic method to discriminate malignant masses from normal tissue in digital mammograms

G. M. t. Brake, N. Karssemeijer, J. H. Hendriks
  • Phys. Med. Biol., 45(10), 2843-2857 (2000).
  • 2000
VIEW 7 EXCERPTS
HIGHLY INFLUENTIAL

Cancer Facts & Figures 2013

American Cancer Society
  • http://www.cancer.org/research/cancerfactsstatistics/cancerfactsfigures2013/index, (2013).
  • 2013
VIEW 1 EXCERPT

Cancer statistics, 2013.

  • CA: a cancer journal for clinicians
  • 2013
VIEW 1 EXCERPT

Gray Level Run Length Matrix Toolbox v1.0

X. Wei
  • Beijing Aeronautical Technology Research Center, http://www.mathworks.com/matlabcentral/fileexchange/17482-gray-level-run-length-matrix-toolbox. Last accessed: 12 December 2013, (2007).
  • 2013
VIEW 1 EXCERPT

Similar Papers

Loading similar papers…