There are indications in the literature that polarimetric observations of neoplastic changes in biological tissues may support early diagnosis of cancer. In the present studies, samples of human breast tissue were observed in a polarized light. The images of healthy and malignant tissues were decomposed by a à trous wavelet algorithm. When a multiscale representation of tissue images is determined, their autocorrelation functions are also compared. A comparison of new observables, multiscale entropy and mean entropy vectors are presented. It was found that these observables might be considered as possible indicators of the malignant transformation in tissue.