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

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.