A NOVEL ENTROPY METHOD FOR CLASSIFICATION OF BIOSIGNALS

Andrea Casanova, Valentina Savona, Sergio Vitulano

Abstract

The paper introduces entropy as a measure for 1D signals. We propose as entropy measure the relationship between the crest of the signal (i.e. its portion contained between the absolute minimum and maximum) and the energy of the signal. A linear transformation of 2D signals into 1D signals is also illustrated. The experimental results are compared to several fuzzy entropy measures and other well-known methods in literature. Experiments have been carried out on medical images from a large mammograms database; this choice is due to the high-degree of difficulty of this kind of images and the strong interest in the scientific community on medical images. The capability of the methods was tested in order to discriminate between benignant and malignant microcalcifications.

References

  1. F. Kossentini, M.J.T. Smith, C.F. Barnes, 1995. Image coding using entropy-constrained residual vector quantization. In IEEE Transactions on Image Processing ,4 , pp.1349-1357
  2. V.Di Gesù, S.Roy, 2000. Fuzzy measures for image distance, in proc of Advances. In Fuzzy Systems and Intelligent Technologies , F.Masulli, R.Parenti, G.Pasi Ed.s, Shaker Publishing , pp.156 -164.
  3. C. Di Ruberto, M. Nappi, S. Vitulano, 1998. Different Methods to Segment Biomedical Images. In Pattern Recognition Letters, 18, nos. 11/13, pp. 1125-1131.
  4. Qian Zhao et alt., 2004. Multi-resolution source coding using Entropy constrained Dithered Scalar Quantization. In Proc. of DCC'04 IEEE.
  5. M. Toews, t. Arbel, 2003. Entropy of likelihood feature selection for image correspondence. In Proc. ICCV'03 IEEE.
  6. Melloul M., Joskowicz L., 2002. Segmentation of microcalcification in X-ray mammograms using entropy thresholding. In CARS 2002, H.U.Lemke et al. Editors.
  7. Kullback S.C., 1959. Information Theory and Statisitcs, New York, N.Y.
  8. E.T.Jaynes, 1962. In Brandies Theor.Phys.Lectures on Statistical Physics, Vol. 3, New York, N.Y.
  9. E.R.Caianiello, 1983. Theories:Lett.Al Nuovo Cimento, Vo.38, 539.
  10. A.Casanova, S.Vitulano, 2004. Entropy As a Feature In The Analysis And Classification Of Signals. In Series on Software Engineering and Knowledge Engineering, N.15 - World Scientific ISBN 981-256-137-4.
  11. Heath M. et alt., 1998. Current status of digital database for screening mammography, (Kluwer Academic Pub.), pp. 457-460.
  12. W.Richardson, 1992. Non linear filtering and multiscale texture discrimination for mammograms. In Mathematical Methods Med. Imag., Proc. SPIE 1768 pp. 293-305.
  13. A. Laine et alt., 1992. Multiscale wavelet representation for mammography feature analysis. In Mathematical Methods Med. Imag., Proc. SPIE 1768 pp. 306-316
  14. W.Qian et alt., 1993. Tree structured non linear filter and wavelet transform for microcalcification segmentation in mammography. In Biomedical Iimage Processing and Biomedical Visualization, Proc. SPIE 1905 pp. 509-520.
  15. Y. Yoshida et alt., 1994. Automated detection of clustered microcalcifications. In digital mammograms using wavelet processing techniques in Medical Imaging, Proc. SPIE 2167pp.868-886.
  16. R.N. Strickland, H.Hahn, 1996. Wavelet Transforms for detecting microcalcifications. In Mammograms IEEE Trans. on Medical imaging, Vol.15, No.2
  17. A.Casanova, V.Savona, S.Vitulano, 2004. The Role Of Entropy. In Signal Analysis And Classification: An Application To Breast Diagnosis Medicon2004, Ischia.
  18. A.Casanova, M.Fraschini, 2003. HER: Application on Information Retrieval. In Series on Software Engineering and Knowledge Engineering Vol. 15: 150-159 ISBN:981-238-587-8.
  19. Vitulano S. et alt,. 2000. A hierarchical representation for content-based image retrieval. In Jour. Of Visual Lang. and Comp., 5, pp. 317-326.
  20. I.W. Bassel, ,1992. Mammographic analysis of calcification Radiol. Clin.No.Amer. , Vol. 30 pp 93- 105.
  21. M. Heath, K.W. Bowyer, D. Kopans et alt., 1998. Current status of the digital Database for Screening Mammography. In Digital Mammography, Kluwer , pp 457-460 Academic Pub.
  22. H. Barman et alt., 1993. Using simple local Fourier domain models for computer-aided analysis of mammograms. In Proc. 8th Scandinavian Conf. Image Anal. Norway pp. 479-486.
Download


Paper Citation


in Harvard Style

Casanova A., Savona V. and Vitulano S. (2005). A NOVEL ENTROPY METHOD FOR CLASSIFICATION OF BIOSIGNALS . In Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO, ISBN 972-8865-31-7, pages 276-281. DOI: 10.5220/0001174102760281


in Bibtex Style

@conference{icinco05,
author={Andrea Casanova and Valentina Savona and Sergio Vitulano},
title={A NOVEL ENTROPY METHOD FOR CLASSIFICATION OF BIOSIGNALS},
booktitle={Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO,},
year={2005},
pages={276-281},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001174102760281},
isbn={972-8865-31-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO,
TI - A NOVEL ENTROPY METHOD FOR CLASSIFICATION OF BIOSIGNALS
SN - 972-8865-31-7
AU - Casanova A.
AU - Savona V.
AU - Vitulano S.
PY - 2005
SP - 276
EP - 281
DO - 10.5220/0001174102760281