Neural classification of abnormal tissue in digital mammography using statistical features of the texture

@article{Christoyianni1999NeuralCO,
  title={Neural classification of abnormal tissue in digital mammography using statistical features of the texture},
  author={Ioanna Christoyianni and Evangelos Dermatas and George K. Kokkinakis},
  journal={ICECS'99. Proceedings of ICECS '99. 6th IEEE International Conference on Electronics, Circuits and Systems (Cat. No.99EX357)},
  year={1999},
  volume={1},
  pages={117-120 vol.1}
}
The authors investigated the efficiency of neural classifiers in recognizing cancer regions of suspicion (ROS) on mammograms. Radial-basis-function (RBF) networks and multilayer perceptron (MLP) neural networks are used to classify ROS including all kinds of abnormalities by processing two types of texture features: statistical descriptors based on high-order statistics and the spatial gray-level dependence (SGLD) matrix. Extensive experiments carried out in the MIAS database have given similar… CONTINUE READING

Citations

Publications citing this paper.
SHOWING 1-10 OF 27 CITATIONS

Particle swarm optimization based feature selection in mammogram mass classification

  • 2012 International Conference on Computerized Healthcare (ICCH)
  • 2012
VIEW 8 EXCERPTS
CITES METHODS & BACKGROUND
HIGHLY INFLUENCED

Novel network architecture and learning algorithm for the classification of mass abnormalities in digitized mammograms

  • Artificial Intelligence in Medicine
  • 2008
VIEW 5 EXCERPTS
CITES METHODS & BACKGROUND
HIGHLY INFLUENCED

Mass Detection in Mammograms

VIEW 2 EXCERPTS
CITES METHODS

References

Publications referenced by this paper.
SHOWING 1-4 OF 4 REFERENCES

Nipper, "Computer-aided tnamtnographic screening lor spiculatcd Icsions," Radiology

W. P. Kcgclmcyer, Jr., +4 authors M.L
  • vol. 191,
  • 1994

Breast canccr missed by mammography "

M. Gigcr Z. Huo, C. Vyhorny, D. Wolverlon, R. Sclmidt, K. Doi
  • Coinpuler - Aided Diagnosis : Automatcd Classification of Maimnographic Mass Lesions " , / ' roc . of the 3 " ' Int
  • 1979

Milbrath, "Breast canccr missed by mammography

I. Martin, M. Moskowitr
  • AJR, Vo1.132
  • 1919

and K . Whccler " Rndial - Basis - Punclioii Based Classification o l cations Using Tcxturc Engineering in Medicine ond Biology Harelick R . " Stalistical and Structural Approachcs to Tcxturc "

C. Bonasso