Abstract
Comparison between contra lateral breast images is one of the effective methods in breast cancer detection. Asymmetric temperature distribution can be an indicator of abnormality. The mutual information is a good measure of nonlinear correlation. It is a measure that captures linear and nonlinear dependencies, without requiring the specification of any kind of model of dependence. Therefore, it is suitable for our abnormality indicator. Although nonparametric windows is a numerically expensive technique but it is accurate. The reason is that nonparametric windows incorporate an interpolation model which enhances the resolution to a highly oversampled image. For our purposes we worked with sixty simulated breast thermal images. It is shown that the more similar the thermal image of right breast to the thermal image of left breast, the closer the normalized mutual information value to one.













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Siegel, R., Howell, J.R., Thermal Radiation Heat Transfer. Hemisphere, Washington, D.C. 1992.
Ng, E.Y.-K., Rajendra Acharya, U., A review of remote-sensing infrared thermography for indoor mass blind fever screening in containing an epidemic. IEEE Eng. Med. Biol. 28(1):76–83, (2009)
Singh, Y., Tumor angiogenesis: clinical implications. Nepal J. Neurosci. 1(1):61–63, 2004.
Uematsu, S., Symmetry of skin temperature comparing one side of the body to the other. Int. J. Thermology 1(1):4–7, 1985.
Qi, H., Kuruganti, P.T., Snyder, W.E., Detecting breast cancer from thermal infrared images by Asymmetry Analysis. Biomedical Engineering Handbook, CRC ch. 27, pp. 1–14, 2006.
Diakides, N., Bronzino, J.D., Medical infrared imaging. CRC Press, Taylor & Francis Group, 2008.
Tan, T.Z., Quek, C., Ng, G.S., Ng, E.Y.K., A novel cognitive interpretation of breast cancer thermography with complementary learning fuzzy neural memory structure. Expert Systems with Applications: An International Journal 33(3):652–666, 2007.
Frize, M., Herry, C.H., Roberge, R., Processing of thermal images to detect breast cancer: comparison with previous work. In proceedings of the second joint 24th annual conference and the annual fall meeting of the biomedical engineering society, IEEE EMBS/BMES Conference, vol. 2, 1159–1160, 2002.
Jakubowska, T., Wiecek, B., Wysocki, M., Drews Peszynski, C., Thermal signatures for breast cancer screening comparative study. Engineering in medicine and biology society, 2003. Proceedings of the 25th Annual International Conference of the IEEE, vol. 2, 1117–1120, 2003.
Schaefer, G., Zavisek, M., Nakashima, T., Thermography based breast cancer analysis using statistical features and fuzzy classification. Pattern Recognit. 42(6):1133–1137, 2009.
Eltonsy, N.H., Elmaghraby, A.S., Tourassi, G.D., Bilateral breast volume asymmetry in screening mammograms as a potential marker of breast cancer: preliminary experience. Image Processing, IEEE Int. Conf. in Image Processing, San Antonio, TX 5:5–8, 2007.
Scutt, D., Lancaster, G.A., Manning, J.T., Breast asymmetry and predisposition to breast cancer. Breast Cancer Res. 8:R14, 2006. doi:10.1186/bcr1388.
Cover, T.M., Thomas, J.A., Elements of information theory. John Wiley & Sons, Inc., 1991.
Rossi, F., Lendasse, A., François, D., Wertz, V., Verleysen, M., Mutual information for the selection of relevant variables in spectrometric nonlinear modeling. Chemometr. Intell. Lab. Syst. 80:215–226, 2006.
Chiu, K.C., Liu, Z.Y., Xu, L., A statistical approach to testing mutual independence of ICA recovered sources. 4th international symposium on independent component analysis and blind signal separation, 751–756, Nara, Japan, April, 2003.
Darbellay, G.A., The mutual information as a measure of statistical dependence. IEEE International Symposium on Information Theory, Ulm, Germany, pp. 405, 1997.
Chen, H.M., Varshney, P., Arora, M.K., A study of joint histogram estimation methods to register multi sensor remote sensing images using mutual information. IEEE Geoscience and Remote Sensing Symposium. 6:4035–4037, 2003.
Josien, P.W., Pluim, J.B., Maintz, A., Viergever, M.A., Mutual information based registration of medical images: a survey. IEEE Trans. Med. Imaging. 22(8):986–1004, 2003.
Manton, K.G., Akushevick, I., Kravchenko, J., Cancer mortality and morbidity patterns in the US population, Statistics for Biology and Health, Springer. 2009.
Kadir, T., Brady, M., Estimating statistics in arbitrary regions of interest. Proc. 16th British Machine Vision Conf. 2:589–598, 2005.
Kadir, T., Brady, M., Nonparametric estimation of probability distributions from sampled signals. Technical Report OUEL No: 2283/05, Robotics Research Laboratory, Oxford U., July, 2005.
Dowson, N., Kadir, T., Bowden, R., Estimating the joint statistics of images using nonparametric windows with application to registration using mutual information. IEEE Trans. Pattern Anal. Mach. Intell. 30(10):1841–1857, 2008.
Papoulis, A., Pillai, S.U., Probability, random variables and stochastic processes. Mc Graw Hill, 4th Edition, 2002.
STImaging, http://www.stimaging.com.au/page2.html, last accessed March, 2010.
Ng, E.Y.K., A review of thermography as promising non invasive detection modality for breast tumors. Int. J. Therm. Sci. 48(2009):849–859, 2008.
Belongie, S., Malik, J., Puzicha, J., Shape matching and object recognition using shape contexts. IEEE Trans. Pattern Anal. Mach. Intell. 24(4):509–522 (2002)
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EtehadTavakol, M., Ng, E.Y.K., Lucas, C. et al. Estimating the Mutual Information Between Bilateral Breast in Thermograms Using Nonparametric Windows. J Med Syst 35, 959–967 (2011). https://doi.org/10.1007/s10916-010-9516-x
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DOI: https://doi.org/10.1007/s10916-010-9516-x