Estimating the Mutual Information Between Bilateral Breast in Thermograms Using Nonparametric Windows

Authors:
M. Etehadtavakol;E. Y. Ng;Caro Lucas;S. Sadri;N. Gheissari
Affiliations:
Electrical and Computer Engineering Department, Isfahan University of Technology, Isfahan, Iran and Medical Image and Signal Processing Research Center, Isfahan University of Medical Science, Isfa ...;School of Mechanical and Aerospace Engineering, College of Engineering, Nanyang Technological University, Singapore, Singapore 639798;Electrical and Computer Engineering Department, University of Tehran, Tehran, Iran;Electrical and Computer Engineering Department, Isfahan University of Technology, Isfahan, Iran and Medical Image and Signal Processing Research Center, Isfahan University of Medical Science, Isfa ...;Electrical and Computer Engineering Department, Isfahan University of Technology, Isfahan, Iran and Medical Image and Signal Processing Research Center, Isfahan University of Medical Science, Isfa ...
Venue:
Journal of Medical Systems
Year:
2011

Citing 5
Cited 0

Elements of information theory

Elements of information theory
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Thermography based breast cancer analysis using statistical features and fuzzy classification

Pattern Recognition

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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.