Microcalcification Segmentation Using Normalized Tsallis Entropy: An Automatic "q" Calculation by Exploiting Type II Fuzzy Sets

This article proposes an alternative approach to Tsallis entropy by considering the nonextensive property of -mammograms. The novel thresholding technique is performed by normalized Tsallis entropy characterized by -another parameter q, which depends on the nonextensiveness of mammogram. In previous studies, q was calculated using the histogram distribution, which can lead to erroneous results when pectoral muscles were included. In the present study, we propose a new technique to calculate q, which is independent of mammogram grades. We use type-II fuzzy sets to find the optimal value of q. The proposed approach has been tested on various images, and the results have demonstrated that the proposed normalized Tsallis entropy approach outperforms the two-dimensional -nonfuzzy approach and conventional Shannon entropy partition approach and can be equally effective as Tsallis entropy. -Moreover, our technique is completely automatic, and trial and error method is avoided as in previous literatures.